a vector of AIC values

logical. Should an explanation about how to read the output be printed? (default = TRUE).

a function

an environment in which to assign the parameters as values (default = .GlobalEnv)

a data object (a data frame or a data.table)

name of the variable that will be on the x axis of the barplot

name of the variable that will be on the y axis of the barplot

a vector of values, each of which represents an instance of either a "success" or "failure" (e.g., c("s", "f", "s", "s", "f", "s"))

which value(s) indicate "successes"?

(optional) which value(s) indicate "failures"? If no input is provided for this argument, then all the non-NA values that are not declared to be "successes" will be treated as "failures".

hypothesized probability of success (default = 0.5)

indicates the alternative hypothesis and must be one of "two.sided", "greater", or "less". You can specify just the initial letter. By default, alternative = "two.sided"

width of the confidence interval (default = 0.95)

number of decimal places to which to round the percentages in the summary table (default = 0)

xmin

xmax

ymin

ymax

vertical

horizontal

open

bracket_shape

thickness

bracket_color

label

label_hjust

label_vjust

label_font_size

label_font_face

label_font_face

label_parse

a character string or a character vector

starting position of the susbtring (default = 1)

ending position of the susbtring (default = 1)

a data object (a data frame or a data.table)

a vector of old variable names (i.e., variable names to change)

a vector of new variable names

If skip_absent = TRUE, old variable names that do not exist in the data set will be skipped (default = TRUE).

If print_summary = TRUE, a summary of old and new variable names will printed. (default = TRUE)

type of the output. If output_type = "dt", the function's output will be a data.table with changed names. If output_type = "summary", the function's output will be a data.table listing old and new variable names. By default, output_type = "dt".

R objects.

The function will test whether each input is of this mode. For example, check_modes(a, mode_to_confirm = "numeric"), the function will check whether the object a is numeric.

a character vector containing names of packages to check

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable (must be a binary variable)

number of decimal places to which to round the chi-squared test statistic (default = 2)

number of decimal places to which to round the p-value from the chi-squared test (default = 3)

number of significant digits to round to (for the table of proportions). By default sigfigs_proportion = 2

logical. Should continuity correction be applied? (default = TRUE)

width of the confidence interval for the odds ratio. Input can be any value less than 1 and greater than or equal to 0. By default, odds_ratio_ci = 0.95. If odds_ratio_ci = TRUE, the default value of 0.95 will be used. If odds_ratio_ci = FALSE, no confidence interval will be estimated for the odds ratio.

number of decimal places to which to round the limits of the odds ratio's confidence interval (default = 2)

logical. Whether the inverse of the odds ratio (i.e., 1 / odds ratio) should be returned.

if TRUE, notify how many rows were removed due to missing values. By default, NA count will be printed only if there are any NA values.

if save_as_png = TRUE, the results will be saved as a PNG file (default = FALSE).

name of the PNG file to be saved. By default, the name will be "chi_sq_" followed by a timestamp of the current time. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour.

width of the PNG file (default = 1600)

height of the PNG file (default = 1200)

the units for the width and height arguments. Can be "px" (pixels), "in" (inches), "cm", or "mm". By default, units = "px".

The nominal resolution in ppi which will be recorded in the png file, if a positive integer. Used for units other than the default. By default, res = 200

The layout argument for arranging section titles and tables using the grid.arrange function.

a data object (a data frame or a data.table)

name of the independent variable (must be a categorical variable)

name of the dependent variable (must be a binary variable)

focal value of the dependent variable whose frequencies will be calculated (i.e., the value of the dependent variable that will be considered a "success" or a result of interest)

If contingency_table = TRUE or if contingency_table = "percentages", the percentage of each binary value within each group will be printed. If contingency_table = "counts", a table of frequencies will be printed. If contingency_table = FALSE, no contingency table will be printed.

number of significant digits that the contingency table's percentage values should be rounded to (default = 2)

logical. If percent_and_total = TRUE, tabulate percentages of the focal DV value and a total count of the two values in DV. By default percent_and_total = FALSE

tabulate percentages of the focal DV value only

tabulate counts of the focal DV value only

number of significant digits to round to

if chi_sq_test_stats = TRUE, chi-squared test statistic and degrees of freedom will be included in the pairwise comparison data.table.

logical. Should continuity correction be applied? (default = TRUE)

if save_as_png = TRUE, the results will be saved as a PNG file (default = FALSE).

name of the PNG file to be saved. By default, the name will be "chi_sq_" followed by a timestamp of the current time. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour.

width of the PNG file (default = 2000)

height of the PNG file (default = 800)

the units for the width and height arguments. Can be "px" (pixels), "in" (inches), "cm", or "mm". By default, units = "px".

The nominal resolution in ppi which will be recorded in the png file, if a positive integer. Used for units other than the default. By default, res = 200

The layout argument for arranging section titles and tables using the grid.arrange function.

a numeric vector

What is the desired confidence level expressed as a decimal? (default = 0.95)

if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.

a data object (a data frame or a data.table)

logical. Whether to remove data from survey preview (default = TRUE)

logical. Whether to remove data from test response (default = TRUE)

names of columns that Qualtrics includes in the data set by default (e.g., "StartDate", "Finished"). Accepting the default value default_cols_by_qualtrics = NULL will set the names to be those that Qualtrics uses as of Dec 25, 2020.

new names for columns that Qualtrics includes in the data set by default (e.g., "StartDate", "Finished"). Accepting the default value default_cols_by_qualtrics_new = NULL will set the names to be those that Qualtrics uses as of Dec 25, 2020 converted to snake_case (e.g., "start_date", "finished").

logical. whether to warn the user if converting character to numeric leads to loss of accuracy. (default = FALSE)

if click_data_cols = "rm", columns containing click data (e.g., "_First Click") will be removed. If click_data_cols = "move_to_right", the columns will be moved to the right (end) of the data set.

if page_submit_cols = "rm", columns containing page submit data (e.g., "_Page Submit"; "response time" data) will be removed. If page_submit_cols = "move_to_right", the columns will be moved to the right (end) of the data set.

a numeric vector

should coefficient of variation be calculated for a "population" or a "sample"?

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

range of the confidence interval for Cohen's d (default = 0.95)

If output_type == "all" or if output_type == "d_and_ci", the output will be a vector of Cohen's d and its confidence interval. If output_type == "d", the output will be Cohen's d. If output_type == "ci", the output will be a vector of the confidence interval around Cohen's d. By default, output_type == "all".

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

If direction == "2_minus_1", Cohen's d will reflect the extent to which the mean of IV level 2 is greater than the mean of IV level 2. If direction == "1_minus_2", Cohen's d will reflect the extent to which the mean of IV level 1 is greater than the mean of IV level 2. By default, direction == "2_minus_1".

range of the confidence interval for Cohen's d (default = 0.95)

If output_type == "all" or if output_type == "d_var_se_and_ci", the output will be a vector of Cohen's d and its variance, SE, and confidence interval. If output_type == "d_se_and_ci", the output will be a vector of Cohen's d and its SE and confidence interval. If output_type == "d_and_ci", the output will be a vector of Cohen's d and its confidence interval. If output_type == "d", the output will be Cohen's d. If output_type == "ci", the output will be a vector of the confidence interval around Cohen's d. If output_type == "se", the output will be the standard error of Cohen's d. By default, output_type == "all".

initial value of the noncentrality parameter for optimization (default = 0). Adjust this value if confidence interval results look strange.

a numeric vector containing values whose mean will be calculated

the true mean

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (measure variable of interest)

if save = TRUE, the plot will be saved as a PNG file.

name of the PNG file to be saved. By default, the name will be "cohen_d_over_n_" followed by a timestamp of the current time. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour.

title of the x-axis for the histogram by group. If xlab = FALSE, the title will be removed. By default (i.e., if no input is given), dv_name will be used as the title.

title of the y-axis for the histogram by group. If ylab = FALSE, the title will be removed. By default (i.e., if no input is given), iv_name will be used as the title.

width of the plot to be saved. This argument will be directly entered as the width argument for the ggsave function within ggplot2 package (default = 16)

height of the plot to be saved. This argument will be directly entered as the height argument for the ggsave function within ggplot2 package (default = 9)

Cohen's d (the input can be a vector of values)

sample size in the first of two group (the input can be a vector of values)

sample size in the second of two group (the input can be a vector of values)

(optional argument) variance of d (the input can be a vector of values). If this argument receives an input, variance of r will be returned as well.

a vector of values in the first of two samples

a vector of values in the second of two samples

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

range of the confidence interval for Cohen's d (default = 0.95)

a data object (a data frame or a data.table)

a character vector containing names of columns, across which to combine data

a character string consisting of numbers separated by commas

a data object (a data frame or a data.table)

another data object (a data frame or a data.table)

list of data objects (data.frame or data.table)

a data object (a data frame or a data.table)

name of the variable whose correlations with two other variables will be compared.

name of the first of the two variables whose correlations with var_1_name will be compared.

name of the second of the two variables whose correlations with var_1_name will be compared.

logical. Should the p value based on a one-tailed t-test? (default = FALSE)

number of decimal places to which to round correlation coefficients (default = 2)

number of decimal places to which to round p-values (default = 3)

number of decimal places to which to round the t-statistic (default = 2)

logical. Should the summary be printed? (default = TRUE)

logical. Should the function return a summary table as an output, as opposed to returning the output through the "invisible" function? (default = FALSE)

a vector of estimated effect sizes

a vector of variances of the effect sizes

logical. Should the statistics be rounded? (default = TRUE)

number of decimal places to which to round p-values (default = 3)

number of decimal places to which to round the standard errors of the difference (default = 2)

number of decimal places to which to round the z-statistic (default = 2)

logical. Should the p-values be rounded in a pretty format (i.e., lower threshold: "<.001"). By default, pretty_round_p_value = TRUE.

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (measure variable of interest)

number of significant digits to round to

statistics to calculate for each group. If stats = "basic", group size, mean, standard deviation, median, minimum, and maximum will be calculated. If stats = "all", in addition to the aforementioned statistics, standard error, 95% confidence and prediction intervals, skewness, and kurtosis will also be calculated. The stats argument can also be a character vector with types of statistics to calculate. For example, entering stats = c("mean", "median") will calculate mean and median. By default, stats = "basic"

Should Welch's t-tests be conducted? By default, welch = TRUE

if cohen_d = TRUE, Cohen's d statistics will be included in the pairwise comparison data.table.

if cohen_d_w_ci = TRUE, Cohen's d with 95% CI will be included in the output data.table.

the name of the method to use to adjust p-values. If adjust_p = "holm", the Holm method will be used; if adjust_p = "bonferroni", the Bonferroni method will be used. By default, adjust_p = "holm"

The use of this argument is deprecated. Use the 'adjust_p' argument instead. If bonferroni = TRUE, Bonferroni tests will be conducted for t-tests or Mann-Whitney tests.

if TRUE, Mann-Whitney test results will be included in the pairwise comparison data.table. If FALSE, Mann-Whitney tests will not be performed.

if t_test_stats = FALSE, t-test statistic and degrees of freedom will be excluded in the pairwise comparison data.table. (default = TRUE)

number of decimal places to which to round p-values (default = 3)

Should a one-way ANOVA be conducted and reported? By default, anova = FALSE, but when there are more than two levels in the independent variable, the value will change such tat anova = TRUE.

number of decimal places to which to round the f statistic (default = 2)

number of decimal places to which to round the t statistic (default = 2)

number of decimal places to which to round the degrees of freedom for t tests (default = 2)

if save_as_png = "all" or if save_as_png = TRUE, the histogram by group, descriptive statistics by group, and pairwise comparison results will be saved as a PNG file.

name of the PNG file to be saved. By default, the name will be "compare_groups_results_" followed by a timestamp of the current time. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour.

title of the x-axis for the histogram by group. If xlab = FALSE, the title will be removed. By default (i.e., if no input is given), dv_name will be used as the title.

title of the y-axis for the histogram by group. If ylab = FALSE, the title will be removed. By default (i.e., if no input is given), iv_name will be used as the title.

a numeric vector with values of the endpoints of the x axis.

a numeric vector indicating the points at which to place tick marks on the x axis.

a vector containing labels for the place tick marks on the x axis.

width of the PNG file (default = 5000)

height of the PNG file (default = 3600)

the units for the width and height arguments. Can be "px" (pixels), "in" (inches), "cm", or "mm". By default, units = "px".

The nominal resolution in ppi which will be recorded in the png file, if a positive integer. Used for units other than the default. By default, res = 300

The layout argument for arranging plots and tables using the grid.arrange function.

if col_names_nicer = TRUE, column names will be converted from snake_case to an easier-to-eye format.

logical. Should the values in the dependent variable be converted to numeric for plotting the histograms? (default = TRUE)

if holm = TRUE, the relevant p values will be adjusted using Holm method (also known as the Holm-Bonferroni or Bonferroni-Holm method)

correlation in the first sample

size of the first sample

correlation in the second sample

size of the first sample

logical. Should the p value based on a one-tailed t-test? (default = FALSE)

(only for displaying purposes) number of decimal places to which to round the p-value (default = 3)

(only for displaying purposes) number of decimal places to which to round the z-score (default = 2)

(only for displaying purposes) number of decimal places to which to round correlation coefficients (default = 2)

logical. Should the summary be printed? (default = TRUE)

type of the output. If output_type = "z", the function's output will be the z-score of the difference between the two correlations. If output_type = "p", the function's output will be the p-value associated with the z-score of the difference between the two correlations. By default, output_type = NULL, and the function will not return any value other than the printed summary.

a data object (a data frame or a data.table)

name of the variable whose values will fill the rows of the contingency table

name of the variable whose values will fill the columns of the contingency table

a vector whose values will fill the rows of the contingency table

a vector whose values will fill the columns of the contingency table

If output_type == "dt" the output will be a contingency table as a data.table object. If output_type == "table" the output will be a contingency table as a table object. If output_type == "df" the output will be a contingency table as a data.frame object. By default, output_type == "table".

a data object (a data frame or a data.table)

a character vector specifying classes of columns that will be converted. For example, if classes = "character", all columns of the class "character" will be converted–if they can be converted. The current version of the function only supports converting character columns to numeric.

logical. whether to warn the user if converting character to numeric leads to loss of accuracy. (default = TRUE)

If print_summary = TRUE, a summary of converted columns will printed. (default = TRUE)

If silent = FALSE, a message regarding conversion for a data.frame will be printed. If silent = TRUE, this message will be suppressed. By default, silent = FALSE.

a character vector

a numeric vector of data values

a numeric vector of data values

(optional) a data object (a data frame or a data.table)

(optional) name of the first variable (if using a data set as an input)

(optional) name of the second variable (if using a data set as an input)

range of the confidence interval for the correlation coefficient. If ci_range = FALSE, no confidence interval will be estimated. By default, ci_range = 0.95.

number of decimal places to which to round correlation coefficients (default = 2)

number of decimal places to which to round p-values (default = 3)

type of the output. If output_type = "dt", the function's output will be a data.table with the results from the correlation analysis. If output_type = "summary", the function's output will be a statement (a string) summarizing the results from the correlation analysis. By default, output_type = "summary"

a data object (a data frame or a data.table)

names of the variables for which to calculate all pairwise correlations

names of the variables that will go on the rows of the correlation matrix

names of the variables that will go on the columns of the correlation matrix

number of decimal places to which to round correlation coefficients (default = 2)

number of decimal places to which to round p-values (default = 3)

which value should be filled in cells of the correlation matrix? If output_type = "r", correlation coefficients; if output_type = "p", p-values; if output_type = "rp", correlation coefficients with significance symbols based on p-values; if output_type = "n", sizes of the samples used to calculate the correlation coefficients. By default, output_type = "rp"

logical. If numbered_cols == TRUE and if identical(row_var_names, col_var_names) == TRUE, then the columns will be numbered instead of containing variable names.

a numeric vector

if output_type = "plot", return a cumulative percentage plot; if output_type = "dt", return a data.table with cumulative percentages. By default, output_type = "plot"

a numeric vector

if output_type = "vector", return a vector of descriptive statistics; if output_type = "dt", return a data.table of descriptive statistics (default = "vector")

number of significant digits to round to (default = 3)

logical. Should the standard errors around the mean be included in the descriptive stats? (default = FALSE)

logical. Should 95% CI be included in the descriptive stats? (default = FALSE)

logical. Should 95% PI be included in the descriptive stats? (default = FALSE)

logical. Should the skewness statistic be included in the descriptive stats? (default = FALSE)

logical. Should the kurtosis statistic be included in the descriptive stats? (default = FALSE)

if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.

if TRUE, print the descriptive stats data.table

a data object (a data frame or a data.table)

name of the variable for which descriptive statistics will be calculated

name(s) of grouping variables

statistics to calculate. If stats = "basic", group size, mean, standard deviation, median, minimum, and maximum will be calculated. If stats = "all", in addition to the aforementioned statistics, standard error, 95% confidence and prediction intervals, skewness, and kurtosis will also be calculated. The stats argument can also be a character vector with types of statistics to calculate. For example, entering stats = c("mean", "median") will calculate mean and median. By default, stats = "all"

number of significant digits to round to

names of columns whose values will be rounded

a character vector of names of packages to keep attached

logical. Should a package be detached even though other attached packages depend on it? By default, force = FALSE

logical. If keep_kim = FALSE, Package 'kim' will be detached along with all other user-installed packages. If keep_kim = TRUE, Package 'kim' will not be detached. By default, keep_kim = FALSE

a vector whose elements will be checked for duplicates

logical. If na.rm = TRUE, NA values in the vector will be removed before searching for duplicates. If na.rm = FALSE, NA values will be included in the search as potentially duplicated values. By default, na.rm = TRUE.

number of significant digits to round to in the percent column of the summary (default = 2)

type of output. If output = "summary", the function's output will be a data.table summarizing duplicated values and their counts. If output = "duplicated_values", the function's output will be a vector of duplicated values. If output = "non_duplicated_values", the function's output will be a vector of non-duplicated values (default = "summary")

a character vector

the number of generations to go back (default = 1)

logical. If silent = TRUE, a message will be printed.

message to print

a data object (a data frame or a data.table)

name of the dependent variable

name of the first independent variable

name of the second independent variable

restrict all analyses to observations having these values for the first independent variable

restrict all analyses to observations having these values for the second independent variable

number of significant digits to which to round values in anova table (default = 3)

if TRUE, conduct a robust ANOVA in addition.

number of bootstrap samples for robust ANOVA. The default is set at 2000, but consider increasing the number of samples to 5000, 10000, or an even larger number, if slower handling time is not an issue.

if TRUE, print a plot and enable returning an output (default = TRUE)

if error_bar = "se"; error bars will be +/-1 standard error; if error_bar = "ci" error bars will be a confidence interval

width of the confidence interval (default = 0.95 for 95 percent confidence interval). This argument will not apply when error_bar = "se"

graphically, width of the segments at the end of error bars (default = 0.13)

thickness of the error bars (default = 1)

should a caption be included to indicate the width of the error bars? (default = TRUE).

colors of the lines connecting means (default = NULL) If the second IV has two levels, then by default, line_colors = c("red", "blue")

types of the lines connecting means (default = NULL) If the second IV has two levels, then by default, line_types = c("solid", "dashed")

thickness of the lines connecting group means, (default = 1)

size of the dots indicating group means (default = 3)

by how much should the group means and error bars be horizontally offset from each other so as not to overlap? (default = 0.13)

a character string for the x-axis title. If no input is entered, then, by default, the first value of iv_name will be used as the x-axis title.

a character string for the y-axis title. If no input is entered, then, by default, dv_name will be used as the y-axis title.

position of the y axis title (default = 0.85). By default, y_axis_title_vjust = 0.85, which means that the y axis title will be positioned at 85% of the way up from the bottom of the plot.

a character for the legend title. If no input is entered, then, by default, the second value of iv_name will be used as the legend title. If legend_title = FALSE, then the legend title will be removed.

position of the legend: "none", "top", "right", "bottom", "left", "none" (default = "right")

output type can be one of the following: "anova_table", "group_stats", "plot", "robust_anova_results", "robust_anova_post_hoc_results", "robust_anova_post_hoc_contrast", "all"

name of the PNG file to be saved. If png_name = TRUE, the name will be "factorial_anova_2_way_" followed by a timestamp of the current time. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour.

width of the PNG file (default = 7000)

height of the PNG file (default = 4000)

the units for the width and height arguments. Can be "px" (pixels), "in" (inches), "cm", or "mm". By default, units = "px".

The nominal resolution in ppi which will be recorded in the png file, if a positive integer. Used for units other than the default. If not specified, taken as 300 ppi to set the size of text and line widths.

The layout argument for arranging plots and tables using the grid.arrange function.

a vector whose elements will be checked for duplicates

logical. If na.rm = TRUE, NA values in the vector will be removed before searching for duplicates. If na.rm = FALSE, NA values will be included in the search as potentially duplicated values. By default, na.rm = TRUE.

number of significant digits to round to in the percent column of the summary (default = 2)

type of output. If output = "summary", the function's output will be a data.table summarizing duplicated values and their counts. If output = "duplicated_values", the function's output will be a vector of duplicated values. If output = "non_duplicated_values", the function's output will be a vector of non-duplicated values (default = "summary")

a (vector of) correlation coefficient(s)

a data object (a data frame or a data.table)

name of the binary independent variable

name of the dependent variable

name of the continuous moderator variable

name of the variables to control for

logical. Should the plot include a p-value for the interaction term?

order of levels in the independent variable for legend. By default, it will be set as levels of the independent variable ordered using R's base function sort.

type of output (default = "reg_lines_plot"). Possible inputs: "interactions_pkg_results", "simple_effects_plot", "jn_points", "regions", "reg_lines_plot"

horizontally and vertically jitter dots by a percentage of the respective ranges of x and y values.

horizontally jitter dots by a percentage of the range of x values

vertically jitter dots by a percentage of the range of y values

opacity of the dots (0 = completely transparent, 1 = completely opaque). By default, dot_alpha = 0.5

size of the dots (default = 4)

font size for the interaction p value (default = 8)

logical. Should the labels for Johnson-Neyman point labels be added to the plot? (default = TRUE)

font size for Johnson-Neyman point labels (default = 8)

a vector of hjust values for Johnson-Neyman point labels. By default, the hjust value will be 0.5 for all the points.

logical. Should vertical lines be drawn at the observed extreme values of the moderator if those values lie in siginificant region(s)? (default = FALSE)

By how much should the label for the interaction p-value be adjusted vertically? By default, interaction_p_vjust = -3)

margin for the plot By default plot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right"). If legend_position = "none", the legend will be removed.

types of the regression lines for the two levels of the independent variable. By default, reg_line_types = c("solid", "dashed")

types of the lines for Johnson-Neyman points. By default, jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points (default = 1.5)

colors for the two values of the independent variable (default = c("red", "blue"))

color of the significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is statistically significant.

opacity for sig_region_color. (0 = completely transparent, 1 = completely opaque). By default, sig_region_alpha = 0.08

color of the non-significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is not statistically significant.

opacity for nonsig_region_color. (0 = completely transparent, 1 = completely opaque). By default, nonsig_region_alpha = 0.08

title of the x axis. By default, it will be set as input for mod_name. If x_axis_title = FALSE, it will be removed.

title of the y axis. By default, it will be set as input for dv_name. If y_axis_title = FALSE, it will be removed.

title of the legend. By default, it will be set as input for iv_name. If legend_title = FALSE, it will be removed.

To how many digits after the decimal point should the p value for the interaction term be rounded? (default = 3)

thickness of the lines of fit (default = 1)

To how many digits after the decimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the binary independent variable

name of the binary dependent variable

name of the continuous moderator variable

logical. Should the plot include a p-value for the interaction term?

order of levels in the independent variable for legend. By default, it will be set as levels of the independent variable ordered using R's base function sort.

order of levels in the dependent variable. By default, it will be set as levels of the dependent variable ordered using R's base function sort.

the Minimum Distance in the unit of the moderator variable that will be used for various purposes, such as (1) to disregard the second Johnson-Neyman point that is different from the first Johnson-Neyman (JN) point by less than the Minimum Distance; (2) to determine regions of significance, which will calculate the p-value of the IV's effect (the focal dummy variable's effect) on DV at a candidate JN point + / - the Minimum Distance. This input is hard to explain, but a user can enter a really low value for this argument (e.g., jn_points_disregard_threshold = 0.1 for a moderator measured on a 100-point scale) or use the default. By default, jn_points_disregard_threshold = range of the moderator / 10000 For example, if the observed moderator values range from 1 to 7 (because it is a 7-point scale), then jn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

type of output (default = "reg_lines_plot"). Possible inputs: "interactions_pkg_results", "simple_effects_plot", "jn_points", "regions", "reg_lines_plot"

How many spotlight analyses should be conducted to plot the predicted values at various values of the moderator? (default = 20)

horizontally jitter dots by a percentage of the range of x values (default = 0)

vertically jitter dots by a percentage of the range of y values (default = 5)

opacity of the dots (0 = completely transparent, 1 = completely opaque). By default, dot_alpha = 0.3

size of the dots (default = 6)

font size for the interaction p value (default = 8)

logical. Should the labels for Johnson-Neyman point labels be added to the plot? (default = TRUE)

font size for Johnson-Neyman point labels (default = 8)

a vector of hjust values for Johnson-Neyman point labels. By default, the hjust value will be 0.5 for all the points.

By how much should the label for the interaction p-value be adjusted vertically? By default, interaction_p_vjust = -3)

margin for the plot By default plot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right"). If legend_position = "none", the legend will be removed.

types of the lines for plotting the predicted values By default, line_types_for_pred_values = c("solid", "dashed")

thickness of the lines for plotting the predicted values (default = 2.5)

types of the lines for Johnson-Neyman points. By default, jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points (default = 1.5)

color of the significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is statistically significant.

opacity for sig_region_color. (0 = completely transparent, 1 = completely opaque). By default, sig_region_alpha = 0.08

color of the non-significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is not statistically significant.

opacity for nonsig_region_color. (0 = completely transparent, 1 = completely opaque). By default, nonsig_region_alpha = 0.08

title of the x axis. By default, it will be set as input for mod_name. If x_axis_title = FALSE, it will be removed.

title of the y axis. By default, it will be set as input for dv_name. If y_axis_title = FALSE, it will be removed.

title of the legend. By default, it will be set as input for iv_name. If legend_title = FALSE, it will be removed.

To how many digits after the decimal point should the p value for the interaction term be rounded? (default = 3)

To how many digits after the decimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the binary independent variable

name of the binary dependent variable

name of the continuous moderator variable

logical. Should the plot include a p-value for the interaction term?

order of levels in the independent variable for legend. By default, it will be set as levels of the independent variable ordered using R's base function sort.

order of levels in the dependent variable. By default, it will be set as levels of the dependent variable ordered using R's base function sort.

the Minimum Distance in the unit of the moderator variable that will be used for various purposes, such as (1) to disregard the second Johnson-Neyman point that is different from the first Johnson-Neyman (JN) point by less than the Minimum Distance; (2) to determine regions of significance, which will calculate the p-value of the IV's effect (the focal dummy variable's effect) on DV at a candidate JN point + / - the Minimum Distance. This input is hard to explain, but a user can enter a really low value for this argument (e.g., jn_points_disregard_threshold = 0.1 for a moderator measured on a 100-point scale) or use the default. By default, jn_points_disregard_threshold = range of the moderator / 10000 For example, if the observed moderator values range from 1 to 7 (because it is a 7-point scale), then jn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

type of output (default = "reg_lines_plot"). Possible inputs: "interactions_pkg_results", "simple_effects_plot", "jn_points", "regions", "reg_lines_plot"

How many spotlight analyses should be conducted to plot the predicted values at various values of the moderator? (default = 20)

horizontally jitter dots by a percentage of the range of x values (default = 0)

vertically jitter dots by a percentage of the range of y values (default = 5)

opacity of the dots (0 = completely transparent, 1 = completely opaque). By default, dot_alpha = 0.3

size of the dots (default = 6)

font size for the interaction p value (default = 8)

font size for Johnson-Neyman point labels (default = 8)

a vector of hjust values for Johnson-Neyman point labels. By default, the hjust value will be 0.5 for all the points.

By how much should the label for the interaction p-value be adjusted vertically? By default, interaction_p_vjust = -3)

margin for the plot By default plot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right"). If legend_position = "none", the legend will be removed.

types of the lines for plotting the predicted values By default, line_types_for_pred_values = c("solid", "dashed")

thickness of the lines for plotting the predicted values (default = 2.5)

types of the lines for Johnson-Neyman points. By default, jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points (default = 1.5)

color of the significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is statistically significant.

opacity for sig_region_color. (0 = completely transparent, 1 = completely opaque). By default, sig_region_alpha = 0.08

color of the non-significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is not statistically significant.

opacity for nonsig_region_color. (0 = completely transparent, 1 = completely opaque). By default, nonsig_region_alpha = 0.08

title of the x axis. By default, it will be set as input for mod_name. If x_axis_title = FALSE, it will be removed.

title of the y axis. By default, it will be set as input for dv_name. If y_axis_title = FALSE, it will be removed.

title of the legend. By default, it will be set as input for iv_name. If legend_title = FALSE, it will be removed.

To how many digits after the decimal point should the p value for the interaction term be rounded? (default = 3)

To how many digits after the decimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the multicategorical independent variable; this variable must have three or more categories.

name of the dependent variable

name of the continuous moderator variable

names of the contrast variables

names of the contrast variables for which floodlight analyses will be conducted

name of the variables to control for

logical. Should the plot include a p-value for the interaction term?

order of levels in the independent variable for legend. By default, it will be set as levels of the independent variable ordered using R's base function sort.

which kind of heteroskedasticity-consistent (robust) standard errors should be calculated? (default = "HC4")

number of decimal places to which to round r-squared values (default = 3)

number of decimal places to which to round the f statistic for model comparison (default = 2)

number of significant digits to round to (for values in the regression tables, except for p values). By default sigfigs = 2

the Minimum Distance in the unit of the moderator variable that will be used for various purposes, such as (1) to disregard the second Johnson-Neyman point that is different from the first Johnson-Neyman (JN) point by less than the Minimum Distance; (2) to determine regions of significance, which will calculate the p-value of the IV's effect (the focal dummy variable's effect) on DV at a candidate JN point + / - the Minimum Distance. This input is hard to explain, but a user can enter a really low value for this argument (e.g., jn_points_disregard_threshold = 0.1 for a moderator measured on a 100-point scale) or use the default. By default, jn_points_disregard_threshold = range of the moderator / 10000 For example, if the observed moderator values range from 1 to 7 (because it is a 7-point scale), then jn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

If print_floodlight_plots = TRUE, a floodlight plot for each dummy variable will be printed. By default, print_floodlight_plots = TRUE

output of the function (default = "all"). Possible inputs: "reg_models", "reg_tables", "reg_tables_rounded", "all"

horizontally jitter dots by a percentage of the range of x values

vertically jitter dots by a percentage of the range of y values

opacity of the dots (0 = completely transparent, 1 = completely opaque). By default, dot_alpha = 0.5

size of the dots (default = 4)

font size for the interaction p value (default = 8)

font size for Johnson-Neyman point labels (default = 6)

a vector of hjust values for Johnson-Neyman point labels. By default, the hjust value will be 0.5 for all the points.

By how much should the label for the interaction p-value be adjusted vertically? By default, interaction_p_vjust = -3)

margin for the plot By default plot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right"). If legend_position = "none", the legend will be removed.

types of the lines of fit for the two levels of the independent variable. By default, line_of_fit_types = c("solid", "dashed")

thickness of the lines of fit (default = 1.5)

types of the lines for Johnson-Neyman points. By default, jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points (default = 1.5)

color of the significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is statistically significant.

opacity for sig_region_color. (0 = completely transparent, 1 = completely opaque). By default, sig_region_alpha = 0.08

color of the non-significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is not statistically significant.

opacity for nonsig_region_color. (0 = completely transparent, 1 = completely opaque). By default, nonsig_region_alpha = 0.08

title of the x axis. By default, it will be set as input for mod_name. If x_axis_title = FALSE, it will be removed.

title of the y axis. By default, it will be set as input for dv_name. If y_axis_title = FALSE, it will be removed.

title of the legend. By default, it will be set as input for iv_name. If legend_title = FALSE, it will be removed.

To how many digits after the decimal point should the p value for the interaction term be rounded? (default = 3)

To how many digits after the decimal point should the jn point labels be rounded? (default = 2)

a data object (a data frame or a data.table)

name of the multicategorical independent variable; this variable must have three or more categories.

name of the dependent variable

name of the continuous moderator variable

name of the coding scheme to use; the current version of the function allows only the "indicator" coding scheme. By default, coding = "indicator"

value of the independent variable that will be the reference value against which other values of the independent variable will be compared

name of the variables to control for

logical. Should the plot include a p-value for the interaction term?

order of levels in the independent variable for legend. By default, it will be set as levels of the independent variable ordered using R's base function sort.

which kind of heteroskedasticity-consistent (robust) standard errors should be calculated? (default = "HC4")

number of decimal places to which to round r-squared values (default = 3)

number of decimal places to which to round the f statistic for model comparison (default = 2)

number of significant digits to round to (for values in the regression tables, except for p values). By default sigfigs = 2

the Minimum Distance in the unit of the moderator variable that will be used for various purposes, such as (1) to disregard the second Johnson-Neyman point that is different from the first Johnson-Neyman (JN) point by less than the Minimum Distance; (2) to determine regions of significance, which will calculate the p-value of the IV's effect (the focal dummy variable's effect) on DV at a candidate JN point + / - the Minimum Distance. This input is hard to explain, but a user can enter a really low value for this argument (e.g., jn_points_disregard_threshold = 0.1 for a moderator measured on a 100-point scale) or use the default. By default, jn_points_disregard_threshold = range of the moderator / 10000 For example, if the observed moderator values range from 1 to 7 (because it is a 7-point scale), then jn_points_disregard_threshold = (7 - 1) / 10000 = 0.0006

If print_floodlight_plots = TRUE, a floodlight plot for each dummy variable will be printed. By default, print_floodlight_plots = TRUE

output of the function (default = "all"). Possible inputs: "reg_models", "reg_tables", "reg_tables_rounded", "all"

horizontally jitter dots by a percentage of the range of x values

vertically jitter dots by a percentage of the range of y values

opacity of the dots (0 = completely transparent, 1 = completely opaque). By default, dot_alpha = 0.5

size of the dots (default = 4)

font size for the interaction p value (default = 8)

font size for Johnson-Neyman point labels (default = 8)

a vector of hjust values for Johnson-Neyman point labels. By default, the hjust value will be 0.5 for all the points.

By how much should the label for the interaction p-value be adjusted vertically? By default, interaction_p_vjust = -3)

margin for the plot By default plot_margin = ggplot2::unit(c(75, 7, 7, 7), "pt")

position of the legend (default = "right"). If legend_position = "none", the legend will be removed.

types of the lines of fit for the two levels of the independent variable. By default, line_of_fit_types = c("solid", "dashed")

thickness of the lines of fit (default = 1.5)

types of the lines for Johnson-Neyman points. By default, jn_line_types = c("solid", "solid")

thickness of the lines at Johnson-Neyman points (default = 1.5)

colors for the two values of the independent variable (default = c("red", "blue"))

color of the significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is statistically significant.

opacity for sig_region_color. (0 = completely transparent, 1 = completely opaque). By default, sig_region_alpha = 0.08

color of the non-significant region, i.e., range(s) of the moderator variable for which simple effect of the independent variable on the dependent variable is not statistically significant.

opacity for nonsig_region_color. (0 = completely transparent, 1 = completely opaque). By default, nonsig_region_alpha = 0.08

title of the x axis. By default, it will be set as input for mod_name. If x_axis_title = FALSE, it will be removed.

title of the y axis. By default, it will be set as input for dv_name. If y_axis_title = FALSE, it will be removed.

title of the legend. By default, it will be set as input for iv_name. If legend_title = FALSE, it will be removed.

To how many digits after the decimal point should the p value for the interaction term be rounded? (default = 3)

To how many digits after the decimal point should the jn point labels be rounded? (default = 2)

default = NULL

default = NULL

default = NULL

default = c(2, 10)

default = 1

default = 0.3

default = NULL

default = NULL

default = NULL

default = NULL

default = 1.2

default = 0.3

default = -0.5

default = "black"

default = NULL

default = NULL

default = 6

default = 0

default = "bold"

default = 0

default = 6

default = "bold"

default = 2

default = "Observed Outcome"

default = 1

default = 0

default = "dotted"

default = 0

default = NULL

default = 60

default = 6

default = "plain"

default = NULL

default = 25

default = 0

default = 6

default = "plain"

default = NULL

default = 6

default = "none"

default = NULL

a numeric vector

the value to which zero or negative values will be converted to. If zero_or_neg_convert_to == NA, zero or negative values will be converted to NA values and thus be excluded when calculating the geometric mean. (default = NA)

a character string of the png file name. By default, if no input is given (name = NULL), the file name will begin with "ggplot". If the desired output file name is "myplot.png", enter name = "myplot", timestamp = FALSE

file name extension (default = "png"). If file_name_extension = "svg", Package svglite needs to be installed.

if timestamp = TRUE, a timestamp of the current time will be appended to the file name. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour. By default, timestamp will be set as TRUE, if no input is given for the name argument, and as FALSE, if an input is given for the name argument.

width of the plot to be saved. This argument will be directly entered as the width argument for the ggsave function within ggplot2 package (default = 16)

height of the plot to be saved. This argument will be directly entered as the height argument for the ggsave function within ggplot2 package (default = 9)

a numeric vector

a numeric vector indicating breaks for the bins. By default, no input is required for this argument.

a numeric vector containing counts for the bins (i.e., heights of the bins). By default, no input is required for this argument.

logical. If percent = TRUE, percentages will be plotted rather than frequencies (default = FALSE).

color of the area inside each bin (default = "green4")

color of the border around each bin (default = "black")

thickness of the border around each bin (default = 1)

if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.

a vector of values at which to place tick marks on the x axis (e.g., setting x_axis_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)

a vector of values at which to place tick marks on the y axis (e.g., setting y_axis_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)

logical. Should the axis lines be capped at the outer tick marks? (default = FALSE)

title for x axis (default = "Value")

title for y axis (default = "Count" or "Percentage", depending on the value of percent)

position of the y axis title (default = 0.85).

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

a character vector indicating the desired presentation order of levels in the independent variable (from the top to bottom). Omitting a group in this argument will remove the group in the set of histograms.

number of bins for the histograms (default = 40)

space between histograms (minimum = 0, maximum = 1, default = 0.15)

logical. Should the baseline and the trailing lines to either side of the histogram be drawn? (default = FALSE)

title of the x-axis for the histogram by group. If xlab = FALSE, the title will be removed. By default (i.e., if no input is given), dv_name will be used as the title.

title of the y-axis for the histogram by group. If ylab = FALSE, the title will be removed. By default (i.e., if no input is given), iv_name will be used as the title.

a numeric vector with values of the endpoints of the x axis.

a numeric vector indicating the points at which to place tick marks on the x axis.

a vector containing labels for the place tick marks on the x axis.

number of significant digits to round to (default = 3)

logical. Should the values in the dependent variable be converted to numeric for plotting the histograms? (default = TRUE)

a numeric vector

number of bins for the histogram (default = 30)

a vector of values at which to place tick marks on the x axis (e.g., setting x_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)

a vector of values at which to place tick marks on the y axis (e.g., setting y_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)

color for inside of the bins (default = "cyan4")

color for borders of the bins (default = "black")

position of the y axis title (default = 0.85).

title for x axis (default = "Value")

title for y axis (default = "Count")

logical. Should the axis lines be capped at the outer tick marks? (default = FALSE)

if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.

a numeric vector

a numeric vector indicating breaks for the bins. By default, no input is required for this argument.

a numeric vector containing counts for the bins (i.e., heights of the bins). By default, no input is required for this argument.

logical. If percent = TRUE, percentages will be plotted rather than frequencies (default = FALSE).

color of the area inside each bin (default = "green4")

color of the border around each bin (default = "black")

thickness of the border around each bin (default = 1)

if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.

a vector of values at which to place tick marks on the x axis (e.g., setting x_axis_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)

a vector of values at which to place tick marks on the y axis (e.g., setting y_axis_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)

logical. Should the axis lines be capped at the outer tick marks? (default = FALSE)

title for x axis (default = "Value")

title for y axis (default = "Count" or "Percentage", depending on the value of percent)

position of the y axis title (default = 0.85).

a numeric vector

cutoff points for bins

logical. Should the leftmost bin treated as an outlier bin? (default = TRUE)

logical. Should the rightmost bin treated as an outlier bin? (default = TRUE)

a vector of values at which to place tick marks on the x axis. Note that the first bar spans from 0.5 to 1.5, second bar from 1.5 to 2.5, ... nth bar from n - 0.5 to n + 0.5. See the example. By default, tick marks will be placed at every cutoff point for bins

a character vector to label tick marks. By default, the vector of cutoff points for bins will also be used as labels.

a vector of values at which to place tick marks on the y axis (e.g., setting y_tick_marks = seq(0, 10, 5) will put tick marks at 0, 5, and 10.)

color to fill inside of the outlier bins (default = "coral")

color to fill inside of the non-outlier bins (default = "cyan4")

color for borders of the bins (default = "black")

position of the y axis title (default = 0.85).

title for x axis (default = "Value"). If x_axis_title = FALSE, x axis title will be removed from the plot.

title for y axis. By default, it will be either "Proportion" or "Count".

if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.

logical. Should proportions be plotted, as opposed to frequencies? (default = TRUE)

logical. Should frequencies be plotted, as opposed to proportions? (default = FALSE). If plot_frequency = TRUE, plot_proportion will switch to be FALSE.

logical. Should mean marked on the histogram? (default = TRUE)

logical. Should 95% confidence interval marked on the histogram? (default = TRUE)

logical. Should median marked on the histogram? (default = TRUE)

position of the median label as a percentage of height of the tallest bin (default = 15)

size of the error bars (default = 3)

a numeric vector of p-values

a list of data.table objects

name of the column that will contain ID values. By default, id_col_name = "id".

position of the newly created ID column. If id_col_position = "first", the new ID column will be placed as the first column in respective data sets. If id_col_position = "last", the new ID column will be placed as the last column in respective data sets.

If silent = TRUE, a summary of starting and ending ID values in each data set will not be printed. If silent = FALSE, a summary of starting and ending ID values in each data set will be printed. (default = FALSE)

two or more R objects. If a vector or list is entered as an input, the function will test whether the vector's or list's elements are identical.

a numeric vector

logical. If unbiased = TRUE, the unbiased estimate of the population kurtosis will be calculated. If unbiased = FALSE, the biased estimate of the population kurtosis will be calculated. By default, unbiase = TRUE.

a vector or a data frame or an array or NULL.

a data object (a data frame or a data.table)

name of the dependent variable

name of the first independent variable

name of the second independent variable

number of decimal places to which to round the F-statistic from Levene's test (default = 2)

number of decimal places to which to round the p-value from Levene's test (default = 3)

If output_type = "text", the output will be the results of Levene's test in a text format (i.e., character). If output_type = "list", the output will be the results of Levene's test in a list format (e.g., p value, F stat, etc. as a list). By default, output_type = "text"

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (binary outcome)

a contingency table, which can be directly entered as an input for calculating the odds ratio

width of the confidence interval. Input can be any value less than 1 and greater than or equal to 0. By default, ci = 0.95. If ci = TRUE, the default value of 0.95 will be used. If ci = FALSE, no confidence interval will be estimated.

logical. Should the output include variance of the log of odds ratio? (default = FALSE)

logical. Whether the inverse of the odds ratio (i.e., 1 / odds ratio) should be returned.

log odds ratio (the input can be a vector of values), which will be converted to Cohen's d

logical. Should the names from the input be removed? (default = TRUE)

a data object (a data frame or a data.table)

name of the dependent variable (must be a binary variable)

name of the first independent variable

name of the second independent variable

number of decimal places to which to round p-values (default = 3)

number of decimal places to which to round chi square statistics (default = 2)

a vector with the ordered levels of the dependent variable, the first and second elements of which will be coded as 0 and 1, respectively, to run logistic regression. E.g., dv_ordered_levels = c("fail", "pass")

(only if the first independent variable is a binary variable) a vector with the ordered levels of the first independent variable, the first and second elements of which will be coded as 0 and 1, respectively, to run logistic regression. E.g., iv_1_ordered_levels = c("control", "treatment")

(only if the second independent variable is a binary variable) a vector with the ordered levels of the first independent variable, the first and second elements of which will be coded as 0 and 1, respectively, to run logistic regression. E.g., iv_2_ordered_levels = c("male", "female")

logical. Should the output simply be a printout of a one-line summary on the interaction term? (default = FALSE)

logical. Should the output simply be a p-value of the interaction term in the logistic regression model? (default = FALSE)

logical. If return_dt_w_binary = TRUE, the function will return a data.table with binary variables coded as 0 or 1 (default = FALSE)

a data object (a data frame or a data.table)

formula for estimating a single logistic regression model

formula for estimating logistic regression model 1 of 2

formula for estimating logistic regression model 2 of 2

logical. Should the z values be kept in the table? (default = FALSE)

logical. Should the row for the constant be cleared except for b and standard error of b? (default = TRUE)

logical. Should the odds ratio columns be combined? (default = TRUE)

number of decimal places to which to round b and standard error of b (default = 3)

number of decimal places to which to round z values (default = 3)

number of decimal places to which to round p-values (default = 3)

number of decimal places to which to round odds ratios (default = 3)

number of decimal places to which to round R-squared values (default = 3)

number of decimal places to which to round model chi-squared values (default = 3)

logical. Should the p-values be rounded in a pretty format (i.e., lower threshold: "<.001"). By default, pretty_round_p_value = TRUE.

logical. Should the default summary output of the glm objects be printed? (default = FALSE)

logical. Should the summaries of logistic regressions in a data table format be printed? (default = TRUE)

logical. Should the comparison of two logistic regression models be printed? (default = TRUE)

If output_type = "summary_dt_list" (default), the output of the function will be summaries of the two logistic regressions in a data.table format. If output_type = "glm_object_list", the output of the function will be the two glm objects estimating logistic regression models. If output_type = "glm_default_summary_list", the output of the function will be the R's default summary output for the two glm objects estimating logistic regression models. If output_type = "model_comparison_stats", the output of the function will be statistics from comparison of the two logistic regression models. If output_type = "all", the output of the function will be a list of the aforementioned outputs.

a glm object estimating a logistic regression model

logical. Should the z values be kept in the table? (default = FALSE)

logical. Should the row for the constant be cleared except for b and standard error of b? (default = TRUE)

logical. Should the odds ratio columns be combined? (default = TRUE)

number of decimal places to which to round b and standard error of b (default = 3)

number of decimal places to which to round z values (default = 3)

number of decimal places to which to round p-values (default = 3)

number of decimal places to which to round odds ratios (default = 3)

number of decimal places to which to round R-squared values (default = 3)

number of decimal places to which to round model chi-squared values (default = 3)

logical. Should the p-values be rounded in a pretty format (i.e., lower threshold: "<.001"). By default, pretty_round_p_value = TRUE.

a data object (a data frame or a data.table)

name of the dependent variable

name of the first independent variable

name of the second independent variable

restrict all analyses to observations having these values for the first independent variable

restrict all analyses to observations having these values for the second independent variable

type of the output. If output_type = "all", the function will return a results summary and print a mosaic plot. (default = "all")

number of decimal places to which to round p-values (default = 3)

number of decimal places to which to round chi-squared test statistics (default = 2)

If mosaic_plot = TRUE, a mosaic plot will be printed (default = TRUE)

If report_as_field = TRUE, reports summary will follow the format suggested by Andy Field (2012) (ISBN: 978-1-4462-0045-2, p. 851)

a numeric vector

the threshold value for determining outliers. If threshold == 2.5, the median plus or minus 2.5 times the MAD will be the cutoff values for determining outliers. In other words, values less than the median minus 2.5 times the MAD and values greater than the median plus 2.5 times the MAD will be considered outliers. By default, threshold == 2.5

scale factor for the 'mad' function in the 'stats' package. It is the constant linked to the assumed distribution. In case of normality, constant = 1.4826. By default, constant == 1.4826.

the value to which outliers will be converted. For example, if convert_outliers_to = NA, the outlier values will be converted to NA values. If convert_outliers_to = 1000, the outlier values will be converted to 1000. By default, convert_outliers_to == NA.

type of the output. If output_type = "converted_vector", the function's output will be a vector with outliers converted to the value set by the argument convert_outliers_to. If output_type = "outliers", the function's output will be outliers in the original vector as determined by the MAD method. If output_type = "cutoff_values", the function's output will be the cutoff values for determining outliers. For example, if outliers will be values less than 0 and greater than 10, the cutoff values will be 0 and 10. If output_type = "non_outlier_values", the function's output will be a vector consisting only of the values that are not outliers; here, the outliers will be removed from the vector, rather than being converted to NA values. By default, output_type = "converted_vector".

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (measure variable of interest)

order of levels in the independent variable. By default, it will be set as levels of the independent variable ordered using R's base function sort.

number of significant digits to round to

a vector of variable names, each of which will be header of a row in the eventual matrix

a vector of variable names, each of which will be header of a column in the eventual matrix

a numeric vector; though not thoroughly tested, the function can accept a matrix as an input.

a data object (a data frame or a data.table)

name of the independent variable

name of the mediator variable

name of the dependent variable

names of covariates to control for

if TRUE, heteroskedasticity-consistent standard errors will be used in quasi-Bayesian simulations. By default, it will be set as FALSE if nonparametric bootstrap is used and as TRUE if quasi-Bayesian approximation is used.

number of bootstrap samples. The default is set at 1000, but consider increasing the number of samples to 5000, 10000, or an even larger number, if slower handling time is not an issue.

number of significant digits to round to

if output_type = "summary_dt", return the summary data.table; if output_type = "mediate_output", return the output from the mediate function in the 'mediate' package; if output_type = "indirect_effect_p", return the p value associated with the indirect effect estimated in the mediation model (default = "summary_dt")

if silent = FALSE, mediation analysis summary, estimation method, sample size, and number of simulations will be printed; if silent = TRUE, nothing will be printed. (default = FALSE)

a list of data.table objects

name(s) of the column(s) that will contain the ID values in the two data tables. The name(s) of the ID column(s) must be identical in the two data tables.

If silent = TRUE, no message will be printed regarding how many ID values and column names were duplicated. If silent = FALSE, messages will be printed regarding how many column names were duplicated. In cases where only one column was used as the 'id' column (which is the most common case), silent = FALSE will also print messages regarding how many input ID values were duplicated. By default, silent = FALSE.

the first data.table which will remain intact

the second data.table which will be joined outside of (around) the first data.table. If there are any duplicated ID values and column names across the two data tables, the cell values in the first data.table will remain intact and the cell values in the second data.table will be discarded for the resulting merged data table.

name(s) of the column(s) that will contain the ID values in the two data tables. The name(s) of the ID column(s) must be identical in the two data tables.

If silent = TRUE, no message will be printed regarding how many ID values and column names were duplicated. If silent = FALSE, messages will be printed regarding how many column names were duplicated. In cases where only one column was used as the 'id' column (which is the most common case), silent = FALSE will also print messages regarding how many input ID values were duplicated. By default, silent = FALSE.

a data object (a data frame or a data.table)

name of the between-group independent variable

names of the columns containing the repeated measures

restrict all analyses to observations having these values for the between-group independent variable

colors of the dots and lines connecting means (default = NULL) If there are exactly two repeated measures, then, by default, colors = c("red", "blue")

if error_bar = "ci" error bars will be a 95% confidence interval; if error_bar = "se", error bars will be +/-1 standard error. By default, error_bar = "ci"

by how much should the group means and error bars be horizontally offset from each other so as not to overlap? (default = 0.13)

a character for the legend title. If no input is entered, then, by default, the legend title will be removed.

inputs for the add parameter of the expand argument. The first and second values respectively determine the amount of space to add to the left and right along the x-axis. By default, x_axis_expansion_add = c(0.2, 0.03) which means that space with the width of 0.2 will be added to the left, and space with the width of 0.03 will be added to the right.

a character string for the x-axis title. If x_axis_title == FALSE, which is the default value, the x-axis title will be removed.

a character string for the y-axis title (default = "Mean"). If x_axis_title == FALSE, the y-axis title will be removed.

output type can be one of the following: "plot", "all"

R objects.

a data object (a data frame or a data.table)

a formula object for the regression equation

(deprecated) a character vector specifying names of variables that will be mean-centered before the regression model is estimated

a character vector specifying names of variables that will be mean-centered before the regression model is estimated

number of significant digits to round to

round to nth digit after decimal (alternative to sigfigs)

number of decimal places to round p values (overrides all other rounding arguments)

logical. Should the p-values be rounded in a pretty format (i.e., lower threshold: "<.001"). By default, pretty_round_p_value = TRUE.

logical. Should only the upper part of the table be returned? By default, return_table_upper_half = FALSE.

number of digits after the decimal both r-squared and adjusted r-squared values should be rounded to (default 3)

number of digits after the decimal the f statistic of the regression model should be rounded to (default 2)

logical. Should the column names of the regression table be made pretty (e.g., change "std_beta" to "Std. Beta")? (Default = TRUE)

If silent = FALSE, a message regarding mean-centered variables will be printed. If silent = TRUE, this message will be suppressed. By default, silent = FALSE.

if save_as_png = TRUE, the regression table will be saved as a PNG file (default = FALSE).

name of the PNG file to be saved. By default, the name will be "mult_reg_" followed by a timestamp of the current time. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour.

width of the PNG file (default = 1600)

height of the PNG file (default = 1200)

the units for the width and height arguments. Can be "px" (pixels), "in" (inches), "cm", or "mm". By default, units = "px".

The nominal resolution in ppi which will be recorded in the png file, if a positive integer. Used for units other than the default. By default, res = 200

the t-statistic associated with the noncentrality parameters

degrees of freedom associated with the noncentrality parameters

initial value of the noncentrality parameter for optimization (default = 0). Adjust this value if results look strange.

width of the confidence interval associated with the noncentrality parameters (default = 0.95)

a data object (a data frame or a data.table)

name of the independent variable (grouping variable)

name of the dependent variable (binary outcome)

a contingency table, which can be directly entered as an input for calculating the odds ratio

width of the confidence interval. Input can be any value less than 1 and greater than or equal to 0. By default, ci = 0.95. If ci = TRUE, the default value of 0.95 will be used. If ci = FALSE, no confidence interval will be estimated.

number of decimal places to which to round the limits of the confidence interval (default = 2)

logical. Whether the inverse of the odds ratio (i.e., 1 / odds ratio) should be returned.

a data.table object

a character value indicating the name of the column by which to order the data.table

a vector indicating a specific order of the values in the column by which to order the data.table.

a numeric vector

a nonnegative constant by which interquartile range (IQR) will be multiplied to build a "fence," outside which observations will be considered outliers. For example, if iqr = 1.5, IQR * 1.5 will be the "fence" outside which observations will be considered to be outliers. By default, iqr = 1.5.

logical. na.rm argument to be passed onto the 'quantile' function in the 'stats' package. If true, any NA and NaN's are removed from x before the quantiles are computed.

type argument to be passed onto the 'quantile' function in the 'stats' package. An integer between 1 and 9 selecting one of the nine quantile algorithms detailed below to be used. Type '?stats::quantile' for details. By default, type = 7

logical. If unique_outliers = TRUE, the function will return the unique outlier values. If unique_outliers = FALSE, the function will return all the outlier values in the vector x. By default, unique_outliers = FALSE.

a number at which the first interval begins (the left INCLUSIVE endpoint of interval 1)

a number at which the first interval ends (the right INCLUSIVE endpoint of interval 1)

a number at which the second interval begins (the left INCLUSIVE endpoint of interval 2)

a number at which the second interval ends (the right INCLUSIVE endpoint of interval 2)

one or more R objects, to be converted to character vectors. This is the same argument that would be used in the paste0 function.

an optional character string to separate the results. Not NA_character_. This is the same argument that would be used in the paste0 function.

logical indicating if zero-length character arguments should lead to the zero-length character(0) after the sep-phase (which turns into "" in the collapse-phase, i.e., when collapse is not NULL). This is the same argument that would be used in the paste0 function.

a vector of package types. By default, package_type = c("base", "recommended")

a data object (a data frame or a data.table)

names of the variables

number of random data sets. If no input is entered, this value will be set as 30 * number of variables.

percentile used in estimating bias (default = 95).

types of the lines connecting eigenvalues. By default, line_types = c("dashed", "solid")

size of the dots denoting eigenvalues (default = 5).

(optional) x coordinate of the label for eigenvalues from randomly generated data.

(optional) y coordinate of the label for eigenvalues from randomly generated data.

(optional) x coordinate of the label for unadjusted eigenvalues

(optional) y coordinate of the label for unadjusted eigenvalues

How much should labels for the eigenvalue curves be offset, as a percentage of the plot's x and y range? (default = 2)

size of the labels for the eigenvalue curves (default = 6).

size of the dots denoting eigenvalues (default = 5).

thickness of the eigenvalue curves (default = 1.5).

position of the y axis title as a proportion of the range (default = 0.8).

size of the plot title (default = 26).

size of the text on the axes (default = 22).

a numeric vector

a data object (a data frame or a data.table)

names of variables for constructing rows

names of variables for constructing columns independent variables

function to perform for each cell in the pivot table

number of significant digits to which to round values in the pivot table (default = 3)

type of output. If output = "dt", the function's output will be a pivot table in a data.table format. If output = "subsets", the function's output will be a list of data tables that are subsets representing each cell in the pivot table. By default, output = "dt"

logical. Should the column names (i.e., v1, v2, ...) be removed in the data table output?

a data object (a data frame or a data.table)

name of the dependent variable

name(s) of the independent variable(s). Up to two independent variables can be supplied.

logical. If na.rm = TRUE, NA values in independent and dependent variables will be removed before calculating group means.

if error_bar = "se"; error bars will be +/-1 standard error, if error_bar = "ci" error bars will be a confidence interval; if error_bar = "pi", error bars will be a prediction interval

width of the confidence or prediction interval (default = 0.95 for 95 percent confidence or prediction interval). This argument will not apply when error_bar = "se"

graphically, width of the segments at the end of error bars (default = 0.13)

thickness of the error bars (default = 1)

should a caption be included to indicate the width of the error bars? (default = TRUE).

logical. Should lines connecting means within each group be drawn? (default = TRUE)

colors of the lines connecting means (default = NULL) If the second IV has two levels, then by default, line_colors = c("red", "blue")

types of the lines connecting means (default = NULL) If the second IV has two levels, then by default, line_types = c("solid", "dashed")

thickness of the lines connecting group means (default = 1)

Deprecated. Use the 'linewidth' argument instead. (default = 1)

size of the dots indicating group means (default = 3)

by how much should the group means and error bars be horizontally offset from each other so as not to overlap? (default = 0.13)

a character string for the x-axis title. If no input is entered, then, by default, the first value of iv_name will be used as the x-axis title.

a character string for the y-axis title. If no input is entered, then, by default, dv_name will be used as the y-axis title.

position of the y axis title (default = 0.85). By default, y_axis_title_vjust = 0.85, which means that the y axis title will be positioned at 85% of the way up from the bottom of the plot.

a character for the legend title. If no input is entered, then, by default, the second value of iv_name will be used as the legend title. If legend_title = FALSE, then the legend title will be removed.

position of the legend: "none", "top", "right", "bottom", "left", "none" (default = "right")

one or more R objects, to be converted to character vectors. Input(s) to this argument will be passed onto the paste0 function.

an optional character string to separate the results. Not NA_character_. Input(s) to this argument will be passed onto the paste0 function.

a numeric vector

if TRUE, NA values will be removed before calculation

names of packages to load and attach, separated by commas, e.g., "ggplot2", data.table. The input can be any number of packages, whose names may or may not be wrapped in quotes.

logical. If pkg_names_as_object = TRUE, the input will be evaluated as one object containing package names. If pkg_names_as_object = FALSE, the input will be considered as literal packages names (default = FALSE).

logical. If silent_if_successful = TRUE, no message will be printed if preparation of package(s) is successful. If silent_if_successful = FALSE, a message indicating which package(s) were successfully loaded and attached will be printed (default = FALSE).

a character vector indicating names of packages to load silently (i.e., suppress messages that get printed when loading the packaged). By default, silent_load_pkgs = NULL

one number or a numeric vector

how many digits after the decimal point should the p-value be rounded to?

if TRUE, output will be a string of mathematical expression including "p", e.g., "p < .01" (default = FALSE)

a (vector of) correlation coefficient(s)

how many digits after the decimal point should the p-value be rounded to? (default = 2)

current number of iteration

iteration number at which the loop begins (default = 1)

iteration number at which the loop ends.

text to add before "Loop Progress..." By default, it is set to be blank, i.e., text_before = ""

if percent = 1, progress level will be printed at every 1 percent progress (default = 1)

if output_method = "cat", progress level will be printed using the 'cat' function; if output_method = "return", progress level will be returned as the output of the function (default = "cat")

a set of values that will count as successes (hits)

a numeric or character vector containing successes (hits) and failures (misses)

if TRUE, NA values will be removed both from vector and values before calculation (default = TRUE).

By default, output_type = "proportion". If output_type = "proportion", the function will return the calculated proportion; if output_type = "se", the function will return the standard error of the sample proportion; if output_type = "dt", the function will return the the data table of proportion and confidence intervals.

If silent = TRUE, no message will be printed regarding number of NA values or confidence interval. (default = FALSE)

confidence level of the returned confidence interval. Input to this argument will be passed onto the conf.level argument in the prop.test function from the default stats package.

a logical indicating whether Yates' continuity correction should be applied where possible (default = TRUE). Input to this argument will be passed onto the correct argument in the prop.test function from the default stats package.

a vector of z values

a vector of sample sizes which will be used to calculate the weights, which in turn will be used to calculate the weighted z.

a character string of the csv file name without the ".csv" extension. For example, if the csv file to read is "myfile.csv", enter name = "myfile"

logical. if head = TRUE, prints the first five rows of the data set.

a character string of the directory containing the csv file, e.g., dirname = "c:/Users/Documents"

optional arguments for the fread function from the data.table package. Any arguments for data.table's fread function can be used, e.g., fill = TRUE, nrows = 100

logical. if head = TRUE, prints the first five rows of the data set.

optional arguments for the fread function from the data.table package. Any arguments for data.table's fread function can be used, e.g., fill = TRUE, nrows = 100

a regular expression provided, a default theme will be used.

a character vector in which to search for regular expression matches, or a data table whose column names will be searched

logical. If silent = FALSE, a report on regular expression matches will be printed. If silent = TRUE, the report on regular expression matches will not be printed. By default, silent = FALSE

logical. Should Perl-compatible regexps be used?

a value whose relative position is to be searched in a vector

a numeric vector

a numeric vector

position of a vector

a single value or a vector of values which will be removed from the target vector

a character or numeric vector

if silent = FALSE, a summary of values removed will be printed; if silent = TRUE, such summary will not be printed. By default, silent = FALSE

a character vector of names of packages to keep

a character vector indicating types of packages to keep. The default, type_of_pkg_to_keep = c("base", "recommended"), keeps all base and recommended packages that come with R when R is installed.

logical. If keep_kim = FALSE, Package 'kim' will be removed along with all other user-installed packages. If keep_kim = TRUE, Package 'kim' will not be removed. By default, keep_kim = FALSE

a data object (a data frame or a data.table)

name of the column identifying participants

names of the columns containing repeated measures (within-subjects variables)

logical. If histograms = TRUE, histograms of the repeated measures will be plotted. If histograms = FALSE, no histograms will be plotted.

number of decimal places to which to round W statistic from Mauchly's test (default = 2)

number of decimal places to which to round the epsilon statistic from Greenhouse-Geisser or Huynh-Feldt correction (default = 2)

number of decimal places to which to round the corrected degrees of freedom for model (default = 2)

number of decimal places to which to round the corrected degrees of freedom for error (default = 2)

number of decimal places to which to round the F statistic (default = 2)

number of decimal places to which to round generalized eta-squared (default = 2)

a data object (a data frame or a data.table)

a vector of old values that need to be replaced

a new value or a vector of new values that will replace the old values

If silent = FALSE, a message will be printed regarding how many values were replaced. If silent = TRUE, no message will be printed regarding how many values were replaced. (default = FALSE)

a data object (a data frame or a data.table)

a formula object for the regression equation

number of significant digits to round to

round to nth digit after decimal (alternative to sigfigs)

number of bootstrap samples. The default is set at 1000, but consider increasing the number of samples to 5000, 10000, or an even larger number, if slower handling time is not an issue.

a numeric vector

number of significant digits to flexibly round to. By default, sigfigs = 3.

a data object (a data frame or a data.table)

name of the variable that will go on the x axis

name of the variable that will go on the y axis

should the correlation be printed in the console? (default = TRUE)

name of the variable that will be used to label individual observations

name of the variable by which to weight the individual observations for calculating correlation and plotting the line of fit

opacity of the dots (0 = completely transparent, 1 = completely opaque)

if TRUE, the correlation and p-value will be annotated at the top of the plot (default = TRUE)

position of the annotated stats, expressed as a percentage of the range of y values by which the annotated stats will be placed above the maximum value of y in the data set (default = 5). This value will be determined relative to the data. If annotate_y_pos_rel = 5, and the minimum and maximum y values in the data set are 0 and 100, respectively, the annotated stats will be placed at 5% of the y range (100 - 0) above the maximum y value, y = 0.05 * (100 - 0) + 100 = 105.

as an alternative to the argument annotate_y_pos_rel, the input for this argument will determine the position of the annotated stats. If annotate_y_pos_abs = 7.5, then the annotated stats will be placed at the y coordinate of 7.5. By default, this argument will be ignored unless it receives an input. That is, by default, the function will use the default value of the annotate_y_pos_rel argument to determine the y coordinate of the annotated stats.

color of the annotated stats (default = "green4").

font size of the annotated stats (default = 6).

font face of the annotated stats (default = "bold").

if line_of_fit_type = "lm", a regression line will be fit; if line_of_fit_type = "loess", a local regression line will be fit; if line_of_fit_type = "none", no line will be fit

if ci_for_line_of_fit = TRUE, confidence interval for the line of fit will be shaded

color of the line of fit (default = "blue")

thickness of the line of fit (default = 1)

color of the dots (default = "black")

alternative label for the x axis

alternative label for the y axis

a numeric vector indicating the positions of the tick marks on the x axis

a numeric vector indicating the positions of the tick marks on the y axis

size of the dots on the plot (default = 2)

size for dots' labels on the plot. If no input is entered for this argument, it will be set as dot_label_size = 5 by default. If the plot is to be weighted by some variable, this argument will be ignored, and dot sizes will be determined by the argument dot_size_range

minimum and maximum size for dots on the plot when they are weighted

horizontally and vertically jitter dots by a percentage of the respective ranges of x and y values.

horizontally jitter dots by a percentage of the range of x values.

vertically jitter dots by a percentage of the range of y values

logical. Should the axis lines be capped at the outer tick marks? (default = TRUE)

name of the variable that will determine colors of the dots

name of the PNG file to be saved. By default, the name will be "scatterplot_" followed by a timestamp of the current time. The timestamp will be in the format, jan_01_2021_1300_10_000001, where "jan_01_2021" would indicate January 01, 2021; 1300 would indicate 13:00 (i.e., 1 PM); and 10_000001 would indicate 10.000001 seconds after the hour.

if save = TRUE, the plot will be saved as a PNG file.

width of the plot to be saved. This argument will be directly entered as the width argument for the ggsave function within ggplot2 package (default = 16)

height of the plot to be saved. This argument will be directly entered as the height argument for the ggsave function within ggplot2 package (default = 9)

a list of scale items (i.e., list of vectors of ratings) to code normally (as opposed to reverse coding).

a list of scale items to reverse code.

if operation = "mean", mean of the scale items will be calculated; if operation = "sum", sum of the scale items will be calculated (default = "mean").

logical. The na.rm argument that will be passed onto the base R's rowMeans or rowSums function (default = FALSE).

logical. If na_summary = TRUE a summary of NA values will be printed; if na_summary = FALSE the summary will not be printed (default = TRUE).

required for reverse coding; the number from which to subtract item ratings when reverse-coding. For example, if the items to reverse code are measured on a 7-point scale, enter reverse_code_minuend = 8.

a numeric vector

Deprecated. By default, NA values will be removed before calculation

if TRUE, notify how many observations were removed due to missing values. By default, NA count will be printed only if there are any NA values.

a vector of percentages; each of the percentage values must be between 0 and 100

a vector of sample sizes; number of observations used to calculate each of the percentage values

a vector of proportions; each of the proportion values must be between 0 and 1

a vector of sample sizes; number of observations used to calculate each of the percentage values

if TRUE, clear the console (default = TRUE)

if TRUE, remove all objects in the global environment (default = TRUE)

if TRUE, set the working directory to the active document in RStudio (default = TRUE)

if TRUE, unload and load the kim package (default = TRUE)

a data object (a data frame or a data.table)

name of the dependent variable (DV)

name of the first independent variable (IV1), whose main effects will be examined in the first set of contrasts

name of the second independent variable (IV2), whose simple effects at each level of IV1 will be examined in the second set of contrasts

ordered levels of IV1

ordered levels of IV2

If print_contrast_table = "weights_sums_and_products", contrasts' weights, sums of the weights and products will be printed. If print_contrast_table = "weights_only", only the contrasts will be printed.

output can be one of the following: "lm_object", "table", "weights_only", "weights_sums_and_products", "all" By default, output = NULL, and there will be no output from the function other than the tables of simple effects and constrasts which will be printed on the console by default.

a data object (a data frame or a data.table)

name of the independent variable (IV)

name of the dependent variable (DV)

name of the moderator variable (MOD)

number of decimal places to which to round the focal values (default = 2)

number of decimal places to which to round coefficients from the regression analysis (default = 2)

number of decimal places to which to round standard error values from the regression analysis (default = 2)

number of decimal places to which to round t statistics from the regression analysis (default = 2)

number of decimal places to which to round p values from the regression analysis (default = 2)

this input will be used only in cases where moderator is continuous. In such cases, what are the focal values of the moderator at which to estimate the effect of IV on DV? By default, values corresponding to the mean of MOD, and mean of MOD +/-1 SD will be used.

a data object (a data frame or a data.table)

name of the independent variable (IV)

name of the dependent variable (DV)

name of the moderator variable (MOD)

number of decimal places to which to round coefficients from the regression analysis (default = 2)

number of decimal places to which to round standard error values from the regression analysis (default = 2)

number of decimal places to which to round t statistics from the regression analysis (default = 2)

number of decimal places to which to round p values from the regression analysis (default = 2)

this input will be used only in cases where MOD is continuous. In such cases, what are the focal values of the MOD at which to estimate the effect of IV on DV? By default, values corresponding to the mean of MOD, and mean of MOD +/-1 SD will be used.

a numeric vector

a character string indicating the type of skewness to calculate. If type = "adjusted", the adjusted Fisher-Pearson standardized moment coefficient will be calculated. If type = "traditional", the traditional Fisher-Pearson coefficient of skewness will be calculated. If type = "pearson_2", the Pearson 2 skewness coefficient will be calculated. By default, type = "adjusted".

a data object (a data frame or a data.table)

name of the binary independent variable (IV)

name of the dependent variable (DV)

name of the continuous moderator variable (MOD)

logical. Should logistic regressions be conducted, rather than ordinary least squares regressions? By default, ordinary least squares regressions will be conducted.

name(s) of the variable(s) to control for in estimating conditional values of the DV.

focal values of the moderator variable at which to estimate IV's effect on DV.

logical. Should the plot include a p-value for the interaction term?

order of levels in the independent variable for legend. By default, it will be set as levels of the independent variable ordered using R's base function sort.

type of output (default = "plot"). Other possible values include "spotlight_results", "dt_for_plotting", "modified_dt"

set colors for the two levels of the independent variable By default, colors = c("red", "blue").

size of the observed_dots (default = 3)

logical. If observed_dots = TRUE, the observed values of all IV, DV, and MOD combinations will be plotted as dots. On top of these dots the spotlight analysis plot will be laid. If observed_dots = FALSE, these dots will not be plotted. By default, observed_dots = FALSE.

logical. If reg_lines = TRUE, the regression lines from regressing DV on MOD at each value of IV will be plotted. If reg_lines = FALSE, these regression lines will not be plotted. By default, observed_dots = FALSE.

thickness of the regression lines (default = 1).

deprecated. Use reg_line_width instead. thickness of the regression lines (default = 1).

logical. Should lines connecting the estimated values of DV be drawn? (default = TRUE)

thickness of the lines connecting the estimated values of DV (default = 1).

ggplot value for shape of the dots at estimated values of DV (default = 15, a square shape).

size of the dots at estimated values of DV (default = 6).

if error_bar = "se"; error bars will be +/-1 standard error, if error_bar = "ci" error bars will be a confidence interval. By default, error_bar = "ci".

width of the confidence interval (default = 0.95 for a 95 percent confidence interval). This argument will not apply when error_bar = "se"

graphically, width of the segments at the end of error bars (default = 0.13)

(default)

thickness of the error bars (default = 1)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

(default)

The first part of the text for labeling simple effects. By default, simp_eff_text_part_1 = "Simple Effect\n"

color for the text indicating p-values of simple effects (default = "black").

font size of the text indicating p-values of simple effects (default = 5).

(default)

(default)

font size for the interaction p value (default = 6)

(default)

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(default)

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(default)

title of the x axis. By default, it will be set as input for mod_name. If x_axis_title = FALSE, it will be removed.

title of the y axis. By default, it will be set as input for dv_name. If y_axis_title = FALSE, it will be removed.

title of the legend. By default, it will be set as input for iv_name. If legend_title = FALSE, it will be removed.

position of the legend (default = "right"). If legend_position = "none", the legend will be removed.

position of the y axis title (default = 0.85). If default is used, y_axis_title_vjust = 0.85, the y axis title will be positioned at 85% of the way up from the bottom of the plot.

To how many digits after the decimal point should the p value for the interaction term be rounded? (default = 3)

horizontally jitter dots by a percentage of the range of x values

vertically jitter dots by a percentage of the range of y values

opacity of the dots (0 = completely transparent, 1 = completely opaque). By default, dot_alpha = 0.2

(default)

(default)

types of the regression lines for the two levels of the independent variable. By default, reg_line_types = c("solid", "dashed")

(default)

margin for the plot By default plot_margin = ggplot2::unit(c(60, 30, 7, 7), "pt")

If silent = FALSE, (various) messages will be printed. If silent = TRUE, the messages will be suppressed. By default, silent = FALSE.

a numeric vector

a data object (a data frame or a data.table)

a formula object for the regression equation

names of binary variables to reverse code

number of significant digits to round to

round to nth digit after decimal (alternative to sigfigs)

number of decimal places to which to round p-values (default = 3)

logical. Should the p-values be rounded in a pretty format (i.e., lower threshold: "<.001"). By default, pretty_round_p_value = TRUE.

logical. Should only the upper part of the table be returned? By default, return_table_upper_half = FALSE.

number of digits after the decimal both r-squared and adjusted r-squared values should be rounded to (default 3)

number of digits after the decimal the f statistic of the regression model should be rounded to (default 2)

logical. Should the column names of the regression table be made pretty (e.g., change "std_beta" to "Std. Beta")? (Default = TRUE)

If update = "force", force updating the package 'kim'. If update = TRUE, compares the currently installed package 'kim' with the most recent version on GitHub and, if the version on GitHub is more recent, ask the user to confirm the update. If confirmed, then update the package. If update = FALSE, skip updating the package. By default, update = "force"

input for the upgrade argument to be passed on to remotes::install_github. One of "default", "ask", "always", "never", TRUE, or FALSE. "default" respects the value of the R_REMOTES_UPGRADE environment variable if set, and falls back to "ask" if unset. "ask" prompts the user for which out of date packages to upgrade. For non-interactive sessions "ask" is equivalent to "always". TRUE and FALSE correspond to "always" and "never" respectively. By default, upgrade_other_pkg = FALSE.

logical. If update = TRUE, runs the function setup_r_env in the package "kim". Type "?kim::setup_r_env" to learn more. By default, setup_r_env = TRUE

a vector of names of packages to load and attach. By default, default_packages = c("data.table", "ggplot2")

a character vector indicating names of packages to load silently (i.e., suppress messages that get printed when loading the packages). By default, silent_load_pkgs = c("data.table", "ggplot2")

a vector or a data frame or an array or NULL.

an argument to be passed onto the 'sort' function (in base R) for controlling the treatment of NA values. If na.last = TRUE, NA values in the data are put last; if na.last = FALSE, NA values are put first; if na.last = NA, NA values are removed. By default, na.last = TRUE

logical. Should the sort be increasing or decreasing? An argument to be passed onto the 'sort' function (in base R). By default, decreasing = FALSE

a data object (a data frame or a data.table)

name of the independent variable

name of the dependent variable

number of significant digits to round to

Should Welch's t-tests be conducted? By default, welch = TRUE

if cohen_d = TRUE, Cohen's d statistics will be included in the output data.table.

if cohen_d_w_ci = TRUE, Cohen's d with 95% CI will be included in the output data.table.

the name of the method to use to adjust p-values. If adjust_p = "holm", the Holm method will be used; if adjust_p = "bonferroni", the Bonferroni method will be used. By default, adjust_p = "holm"

The use of this argument is deprecated. Use the 'adjust_p' argument instead. If bonferroni = TRUE, Bonferroni tests will be conducted for t-tests or Mann-Whitney tests.

if TRUE, Mann-Whitney test results will be included in the output data.table. If FALSE, Mann-Whitney tests will not be performed.

this is the input for the 'exact' argument used in the 'stats::wilcox.test' function, which conducts a Mann-Whitney test. By default, mann_whitney_exact = FALSE. If you want to use the default settings for the 'stats::wilcox.test' function, consider setting mann_whitney_exact = TRUE.

if t_test_stats = TRUE, t-test statistic and degrees of freedom will be included in the output data.table. By default, t_test_stats = TRUE

if sd = TRUE, standard deviations will be included in the output data.table.

number of decimal places to which to round p-values (default = 3)

Should a one-way ANOVA be conducted and reported? By default, anova = FALSE, but when there are more than two levels in the independent variable, the value will change such tat anova = TRUE.

number of decimal places to which to round the f statistic (default = 2)

number of decimal places to which to round the t statistic (default = 2)

number of decimal places to which to round the degrees of freedom for t tests (default = 2)