Package 'CTTvis'

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)

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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)

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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)

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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)

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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)

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