montecarlo {lordif}R Documentation

performs Monte Carlo simulations for empirical cutoff thresholds

Description

Performs Monte Carlo simulations using multiple datasets without DIF.

Usage

montecarlo(obj, alpha = 0.01, nr = 100)

Arguments

obj an object returned from lordif
alpha desired significance level (e.g., .01)
nr number of replications

Details

The simulated datasets have the same dimensions as the empirical data. Group differences (impact) in theta between groups are preserved in simulated datasets. Returns empirical thresholds for various statistics and effect size measures.

Value

Returns a data frame with the following components:

chi12 prob associated with the LR Chi-square test comparing Model 1 vs. 2
chi13 prob associated with the LR Chi-square test comparing Model 1 vs. 3
chi23 prob associated with the LR Chi-square test comparing Model 2 vs. 3
pseudo12.CoxSnell Cox & Snell pseudo R-square change from Model 1 to 2
pseudo13.CoxSnell Cox & Snell pseudo R-square change from Model 1 to 3
pseudo23.CoxSnell Cox & Snell pseudo R-square change from Model 2 to 3
pseudo12.Nagelkerke Nagelkerke pseudo R-square change from Model 1 to 2
pseudo13.Nagelkerke Nagelkerke pseudo R-square change from Model 1 to 3
pseudo23.Nagelkerke Nagelkerke pseudo R-square change from Model 2 to 3
pseudo12.McFadden McFadden pseudo R-square change from Model 1 to 2
pseudo13.McFadden McFadden pseudo R-square change from Model 1 to 3
pseudo23.McFadden McFadden pseudo R-square change from Model 2 to 3
beta12 proportional beta change from Model 1 to 2
alpha significance level
nr number of replications
cutoff thresholds for the statistics

Note

nr must be a large number (e.g., 500) for smooth distributions.

Author(s)

Seung W. Choi <s-choi@northwestern.edu>

References

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.

See Also

lordif

Examples

##run lordif first
## Not run: age.dif <- lordif(Anxiety[paste("R",1:29,sep="")],Anxiety$age)
##the following takes a long time
## Not run: mc1 <- montecarlo(age.dif,alpha=0.05,nr=500)

[Package lordif version 0.1-4 Index]