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Simulated data set with 100 persons, 10 items and 3 (standardized) covariates. Items 1, 2 and 3 are DIF items.
data(simul.data)
Item1
Item 1, DIF item
Item2
Item 2, DIF item
Item3
Item 3, DIF item
Item4
Item 4, non-DIF item
Item5
Item 5, non-DIF item
Item6
Item 6, non-DIF item
Item7
Item 7, non-DIF item
Item8
Item 8, non-DIF item
Item9
Item 9, non-DIF item
Item10
Item 10, non-DIF item
CovBin1
Binary covariate (standardized)
CovBin2
CovMet
Metric covariate (standardized)
Gunther Schauberger gunther.schauberger@tum https://www.sg.tum.de/epidemiologie/team/schauberger/
Schauberger, Gunther and Tutz, Gerhard (2016): Detection of Differential Item Functioning in Rasch Models by Boosting Techniques, British Journal of Mathematical and Statistical Psychology, 69(1), 80 - 103
DIFboost, print.DIFboost
DIFboost
print.DIFboost
if (FALSE) { data(simul.data) Y <- simul.data[,1:10] X <- simul.data[,11:13] m1 <- DIFboost(Y = Y, X = X) print(m1) }
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