montecarlo {lordif} | R Documentation |
Performs Monte Carlo simulations using multiple datasets without DIF.
montecarlo(obj, alpha = 0.01, nr = 100)
obj |
an object returned from lordif |
alpha |
desired significance level (e.g., .01) |
nr |
number of replications |
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.
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 |
nr must be a large number (e.g., 500) for smooth distributions.
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) ##the following takes a long time ## Not run: mc1 <- montecarlo(age.dif,alpha=0.05,nr=500)