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lordif (version 0.3-3)

Logistic Ordinal Regression Differential Item Functioning using IRT

Description

Analysis of Differential Item Functioning (DIF) for dichotomous and polytomous items using an iterative hybrid of ordinal logistic regression and item response theory (IRT).

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Version

Install

install.packages('lordif')

Monthly Downloads

1,247

Version

0.3-3

License

GPL (>= 2)

Maintainer

Seung W Choi

Last Published

March 3rd, 2016

Functions in lordif (0.3-3)

montecarlo

performs Monte Carlo simulations to generate empirical distributions

DFIT

calculates DFIT statistics

probgrm

calculates item response probabilities according to GRM

plot.lordif

Plot method for lordif class

plot.lordif.MC

Plot method for Monte Carlo simulation output

equate

performs Stocking-Lord Equating

probgpcm

calculates item response probabilities according to GPCM

recode

recodes item responses

extract

extracts IRT item parameters

calctheta

calculates EAP theta estimates and associated standard errors

collapse

collapses response categories

lordif

performs Logistic Ordinal Regression Differential Item Functioning using IRT

separate

splits item response vectors of DIF items by group

Anxiety

A Measure of Anxiety

calcprob

calculates item response probabilities

permute

performs permutation test for empirical cutoff thresholds

runolr

runs ordinal logistic regression models

rundif

runs ordinal logistic regression DIF

tcc

computes a test characteristic curve (tcc)

getcutoff

determines a cutoff threshold

lordif-package

Logistic Ordinal Regression Differential Item Functioning using IRT