permute {lordif}

performs permutation test for empirical cutoff thresholds

Description

performs permutation tests under no-DIF conditions to generate empirical distributions of DIF statistics

Usage

permute(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 vector of group designations is randomly shuffled nr times to estimate the sampling distribution of the statistics when the null hypothesis is true. Returns empirical distributions and thresholds for various statistics and effect size measures.

Value

Returns an object (list) of class "lordif.MC" with the following components:

call

calling expression

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 integer (e.g., 500) for smooth distributions.

Author(s)

Seung W. Choi <[e-mail]>

References

Choi, S. W., Gibbons, L. E., Crane, P. K. (2011). lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations. Journal of Statistical Software, 39(8), 1-30. URL http://www.jstatsoft.org/v39/i08/.

See Also

montecarlo, lordif

Examples

##load PROMIS Anxiety sample data (n=766)
## Not run: data(Anxiety)
##age : 0=younger than 65 or 1=65 or older
##run age-related DIF on all 29 items (takes about a minute)
## Not run: age.DIF <- lordif(Anxiety[paste("R",1:29,sep="")],Anxiety$age)
##the following takes several minutes
## Not run: age.DIF.MC <- permute(age.DIF,alpha=0.01,nr=100)