difR (version 3.2)

LRT: Likelihood-Ratio Test DIF statistic

Description

Calulates Likelihoo-Ratio Test (LRT) statistics for DIF detection.

Usage

LRT(data, member)

Arguments

data

numeric: the data matrix (one row per subject, one column per item).

member

numeric: the vector of group membership with zero and one entries only. See Details.

Value

• A vector with the values of the LRT DIF statistics.

Details

This command computes the likelihood-ratio test statistic (Thissen, Steinberg and Wainer, 1988) in the specific framework of differnetial item functioning. It forms the basic command of difLRT and is specifically designed for this call. The data are passed through the data argument, with one row per subject and one column per item. Missing values are not allowed. The vector of group membership, specified with member argument, must hold only zeros and ones, a value of zero corresponding to the reference group and a value of one to the focal group. The LRT DIF statistic is computed for each item separately, using all other items as anchor items.

References

Bates, D. and Maechler, M. (2009). lme4: Linear mixed-effects models using S4 classes. R package version 0.999375-31. http://CRAN.R-project.org/package=lme4 Magis, D., Beland, S., Tuerlinckx, F. and De Boeck, P. (2010). A general framework and an R package for the detection of dichotomous differential item functioning. Behavior Research Methods, 42, 847-862. Thissen, D., Steinberg, L. and Wainer, H. (1988). Use of item response theory in the study of group difference in trace lines. In H. Wainer and H. Braun (Eds.), Test validity. Hillsdale, NJ: Lawrence Erlbaum Associates.

See Also

difLRT, dichoDif

Examples

# Loading of the verbal data
 data(verbal)
 attach(verbal)

 # Excluding the "Anger" variable
 verbal<-verbal[colnames(verbal)!="Anger"]

 # Keeping the first 5 items and the first 50 subjects
 # (this is an artificial simplification to reduce the computational time)
 # Sixth column holds the group membership
 verbal<-verbal[1:50,c(1:5,25)]

 # Likelihood-ratio statistics
 LRT(verbal[,1:5],verbal[,6])