| Type: | Package |
| Title: | Visualize Item Metrics of the Classical Test Theory Framework |
| Version: | 0.1.1 |
| Description: | Visualizes results of item analysis such as item difficulty, item discrimination, and coefficient alpha for ease of result communication. |
| License: | GPL-3 |
| URL: | https://github.com/TaridWong/CTTvis |
| Depends: | R (≥ 4.3) |
| Imports: | CTT (≥ 2.3.3) |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.3.2 |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| VignetteBuilder: | knitr |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2024-12-17 05:21:11 UTC; tarid |
| Author: | Tarid Wongvorachan
 [aut, cre,
cph] |
| Maintainer: | Tarid Wongvorachan <taridwongvorachan@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2024-12-17 21:20:02 UTC |
coefficient_alpha_visualization
Description
plotting results of coefficient alpha analysis from the Classical test theory framework. Items that increase the overall coefficient alpha when dropped will be shown above the overall alpha line. This helps identifying items that could be revised or removed based on its influence to unidimensional coefficient alpha reliability of the test.
This function can also be used with polytomous item responses. However, it is recommended for users to perform reverse coding as necessary before implementing this function.
Usage
coefficient_alpha_plot(responses, title = "Coefficient Alpha", alpha_round = 3)
Arguments
responses |
A dichotompus item response object (a dataframe or a matrix) |
title |
Title of the plot |
alpha_round |
Rounding option for coefficient alpha. default to 4 decimal points. |
Value
A data frame sorted by coefficient alpha if dropped in ascending order. A plot of coefficient alpha of each item in relation to the overall coefficient alpha.
Examples
data(reliability_df)
# To plot coefficient alpha with the overall alpha rounding of 3 decimal places
coefficient_alpha_plot(responses = reliability_df,
title = "Coefficient Alpha Plot", alpha_round = 3)
dichotomous item responses
Description
A simulated dataset for dichotomous item responses. Percent correct of responses ranges from 0.2 to 0.95. N = 100. Number of items = 10.
Usage
data(dichotomous_response)
Format
An object of class "data.frame"
References
This data set was artificially created for the CTTvis package.
Examples
data(dichotomous_response)
head(dichotomous_response)
item_difficulty_visualization
Description
plotting results of item difficulty analysis from the Classical test theory framework
Usage
difficulty_plot(
responses,
title = "Item Difficulty",
easyFlag = 0.9,
hardFlag = 0.5
)
Arguments
responses |
A dichotomous item response object (a dataframe or a matrix) |
title |
Title of the plot |
easyFlag |
threshold of the easy item |
hardFlag |
threshold of the hard item |
Value
A data frame sorted by item difficulty in ascending order. A plot of item difficulty in relation to the specified threshold.
Examples
data(dichotomous_response)
# To plot item difficulty with easyFlag of .9 and hardFlag of .5
difficulty_plot(responses = dichotomous_response,
title = "Item Difficulty Plot", easyFlag = .90, hardFlag = .50)
point_biserial_visualization
Description
plotting results of item discrimination analysis from the Classical test theory framework
Usage
point_biserial_plot(
responses,
title = "Item Discrimination",
pBis_threshold = 0.2
)
Arguments
responses |
A dichotompus item response object (a dataframe or a matrix) |
title |
Title of the plot |
pBis_threshold |
Threshold of the point-biserial correlation (pBis) |
Value
A data frame sorted by item discrimination in ascending order. A plot of item discrimination in relation to the specified threshold.
Examples
data(dichotomous_response)
# To plot item discrimination with pBis threshol of .20.
point_biserial_plot(responses = dichotomous_response,
title = "Item Discrimination Plot", pBis_threshold = 0.20)
reliability dataframe
Description
A simulated dataset for reliability analysis testing. Each item varies in terms of their influence on the overall reliability if dropped from the test. N = 100. Number of items = 10.
Usage
data(reliability_df)
Format
An object of class "data.frame"
References
This data set was artificially created for the CTTvis package.
Examples
data(reliability_df)
head(reliability_df)