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Last data update: 2014.03.03

R: calculates DFIT statistics

DFIT	R Documentation

calculates DFIT statistics

Description

Calculates DFIT statistics using an object of class "lordif"

Usage

  DFIT(obj)

Arguments

obj

an object of class "lordif"

Details

Calculates DFIT statistics, including the compensatory differential item functioning (CDIF), the non-compensatory differential item functioning (NCDIF), and the differential test functioning (DTF), based on an object returned from lordif.

Value

`CDIF`	a data frame of dimension ni by (ng-1), containing compensatory differential item functioning statistics for ni items and (ng-1) groups
`NCDIF`	a data frame containing non-compensatory differential item functioning statistics
`DTF`	the Differential Test Functioning (DTF) statistic (Raju, van der Linden, & Fleer, 1995)
`ipar`	a list of item parameter estimates by group
`TCC`	a list of test characteristic functions by group

Author(s)

Seung W. Choi <choi.phd@gmail.com>

References

Oshima, T., & Morris, S. (2008). Raju's differential functioning of items and tests (DFIT). Educational Measurement: Issues and Practice, 27, 43-50.

Raju, N. S., van der Linden, W. J., & Fleer, P. F., (1995). An IRT-based internal measure of test bias with application of differential item functioning. Applied Psychological Measurement, 19, 353-368.

Examples

##load PROMIS Anxiety sample data (n=766)
## Not run: data(Anxiety)
##age : 0=younger than 65 or 1=65 or older
##run age-related DIF on all 29 items (takes about a minute)
## Not run: age.DIF <- lordif(Anxiety[paste("R",1:29,sep="")],Anxiety$age)
##run DFIT
## Not run: age.DIF.DFIT <- DFIT(age.DIF)