plotDIF {lordif} | R Documentation |
plots diagnostic graphs for items identified as displaying DIF
plotDIF(obj, labels = c("Reference", "Focal"), cexp = 0.8, lwd = 1)
obj |
output from lordif |
labels |
labels for group levels, e.g., c("Male","Female") |
cexp |
character expansion factor, e.g., cexp=2 for two times a normal size |
lwd |
line width, e.g., lwd=2 for thicker lines for focal groups |
Generates the following graphs IF there is one or more DIF items: 1. Trait Distributions - density graphs for groups 2. Item True Score Functions - true score functions by theta for groups 3. Differences in Item True Score Functions - unsigned differences 4. Item Response Functions - item response function for groups 5. Impact (Weighted by Density) - unsigned differences weighted by theta distributions for the focal group 6. Comparison of TCCs by group based on all items and DIF items 7. Impact on Theta Estimates - theta estimates by group before and after accounting for DIF
Graphs 2-5 are generated for each DIF item Graphs 1, 6 and 7 are generated for the whole analysis
Returns no object.
Runs only if obj contains DIF items.
Seung W. Choi <s-choi@northwestern.edu>
Choi, S. W., Gibbons, L. E., & Crane, P. K. (under review). Development of an iterative hybrid ordinal logistic regression/IRT DIF: A Monte Carlo simulation approach for determining cutoff values. Behavior Research Methods.
##run lordif first ## Not run: age.dif <- lordif(Anxiety[paste("R",1:29,sep="")],Anxiety$age) ## Not run: plotDIF(age.dif,labels=c("Younger","Older"))