difR (version 6.1.0)

LassoData: Rearrange the data matrix for the Detection of DIF using the Lasso Approach (Magis et al. (2015)

Description

A Function that rearrange the matrix to use the lasso DIF detection for dichotomous items.

Usage

LassoData(Data, group)

Value

A matrix of five columns where, respectively,:

SCORE

is the total score.

GROUP

is the group membership.

PERS

is the number of the respondent.

Y

is the dichotomous answer to the item. Only "0" and "1" are allowed.

ITEM

is the item name (must be a character).

Arguments

Data

numeric: either the data matrix only, or the data matrix plus the vector of group membership.

group

numeric or character: either the vector of group membership or the column indicator (within Data) of group membership.

Author

Sebastien Beland
Faculte des sciences de l'education
Universite de Montreal (Canada)

Carl F. Falk
Department of Psychology
McGill University (Canada)
, https://www.mcgill.ca/psychology/carl-f-falk

Details

This function rearranges the data matrix for use in lasso-based DIF detection with dichotomous items. It requires a matrix of dichotomous item responses and a vector indicating group membership.

References

Magis, D., Tuerlinckx, F., & De Boeck, P. (2015). Detection of Differential Item Functioning Using the Lasso Approach. Journal of Educational and Behavioral Statistics, 40(2), 111–135. https://doi.org/10.3102/1076998614559747

Examples

if (FALSE) {

# Example with the verbal data

data(verbal)

LassoData(Data=verbal[,1:24], group=verbal[,26])

# Example with SimDichoDif to generate uniform DIF

It   <- 15 # number of items
ItDIFa <- NULL
ItDIFb <- c(1,3)
NR   <- 100 # number of responses for group 1 (reference)
NF   <- 100 # number of responses for group 2 (focal)
a    <- rep(1,It)          
b    <- rnorm(It,1,.5)  
Gb   <- rep(2,2)           # Group value for U-DIF
Ga   <- 0                  # Group value for NU-DIF: need to be fix to 0 for U-DIF
Out1 <- SimDichoDif(It,ItDIFa,ItDIFb,NR,NF,a,b,Ga,Gb)
Data<-Out1$data[,1:15]
Member<-Out1$data[,16]

LassoData(Data=Data, group=Member)

 }