lordif (version 0.3-3)

DFIT: calculates DFIT statistics

Description

Calculates DFIT statistics using an object of class "lordif"

Usage

DFIT(obj)

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

Arguments

obj

an object of class "lordif"

Author

Seung W. Choi <[e-mail]>

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.

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.

See Also

lordif

Examples

##load PROMIS Anxiety sample data (n=766)
if (FALSE) data(Anxiety)
##age : 0=younger than 65 or 1=65 or older
##run age-related DIF on all 29 items (takes about a minute)
if (FALSE) age.DIF <- lordif(Anxiety[paste("R",1:29,sep="")],Anxiety$age)
##run DFIT
if (FALSE) age.DIF.DFIT <- DFIT(age.DIF)