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lordif (version 0.1-1)

lordif-package: Logistic 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).

Arguments

Details

ll{ Package: lordif Type: Package Version: 0.1-1 Date: 2009-03-08 License: GPL (>=2) LazyLoad: yes } Ordinal logistic regression (OLR) provides a flexible framework for detecting various types of DIF. Previous efforts extended the framework by substituting the matching variable based on sum scores with IRT based trait scores and by employing an iterative process of purifying the matching variable with the use of group-specific item parameters (Crane et. al., 2006). This package represents an effort to integrate both statistical and IRT procedures into a single program. A Monte Carlo simulation approach was incorporated to derive empirical threshold values for various DIF statistics and effect size measures. The three most important functions are: lordif, plotDIF, and montecarlo.

References

Choi, S. W., Gibbons, L. E., & Crane, P. K. (April, 2009). Development of freeware for an iterative hybrid ordinal logistic regression/IRT DIF. Paper Presented at the National Council of Measurement in Education. San Diego, CA. Crane, P. K., Gibbons, L. E., Jolley, L., & van Belle, G. (2006). Differential item functioning analysis with ordinal logistic regression techniques: DIF detect and difwithpar. Medical Care, 44(11 Suppl 3), S115-S123.

See Also

ltm, Design

Examples

Run this code
##data(Anxiety)
##age : 0=younger than 65 and 1=65 or older
##gender: 0=Male and 1=Female
##education: 0=some college or higher 1=high school of lower
#runs age DIF on all 29 items (takes about a minute)
age.dif <- lordif(Anxiety[paste("R",1:29,sep="")],Anxiety$age) 
#generates plots for DIF items, reference="Younger" & focal="Older"
plotDIF(sample.run,labels=c("Younger","Older")) 
montecarlo(age.dif,alpha=0.05,nr=500) 
##this takes about 10 minutes on my computer

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