DistractorAnalysis: Function for item distractor analysis

Description Usage Arguments Details Author(s) Examples

Description

Performs distractor analysis for each item and optional number of groups.

Usage

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DistractorAnalysis(data, key, p.table = FALSE, num.groups = 3, matching = NULL)

Arguments

data

character: data matrix or data frame. See Details.

key

character: answer key for the items.

p.table

logical: should the function return the proportions. If FALSE (default) the counts are returned.

num.groups

numeric: number of groups to that should be respondents splitted.

matching

numeric: numeric vector. If not provided, total score is calculated and distractor analysis is performed based on it.

Details

This function is adapted version of distractor.analysis function from CTT package. The scores are calculatede using the item data and key. The respondents are then splitted into the num.groups-quantiles and the number (or proportion) of respondents in each quantile is reported with respect to their answers.

The data is a matrix or data frame whose rows represents unscored item response from a multiple-choice test and columns correspond to the items.

The key must be a vector of the same length as ncol(data).

Author(s)

Adela Drabinova
Institute of Computer Science, The Czech Academy of Sciences
Faculty of Mathematics and Physics, Charles University
drabinova@cs.cas.cz

Patricia Martinkova
Institute of Computer Science, The Czech Academy of Sciences
martinkova@cs.cas.cz

Examples

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## Not run: 
# loading 100-item medical admission test data
data(dataMedicaltest, dataMedicalkey)

# distractor analysis for dataMedicaltest data set
DistractorAnalysis(dataMedicaltest, dataMedicalkey)

# distractor analysis for dataMedicaltest data set with proportions
DistractorAnalysis(dataMedicaltest, dataMedicalkey, p.table = T)

# distractor analysis for dataMedicaltest data set for 6 groups
DistractorAnalysis(dataMedicaltest, dataMedicalkey, num.group = 6)

## End(Not run)

kitdouble/ShinyIRT documentation built on May 3, 2019, 5:47 p.m.