llbt.fit {prefmod}R Documentation

Function to fit an LLBT

Description

Function to fit an LLBT using an ELIMINATE feature

Usage

llbt.fit(y, Xmodel, q, ncat, maxiter = 100)

Arguments

y response , usually counts
Xmodel design matrix
q number of parameters to eliminate (usually number of comparisons times number of subject covariate levels
ncat number of response categories
maxiter nmaximum number of iterations (default 100)

Details

Be careful when specifying the design matrix. Since there is no extrinsic aliasing the matrix msut have full rank. Usually, one of the design columns for object must be left out.

Author(s)

Reinhold Hatzinger

References

Reinhold Hatzinger, Brian J. Francis: Fitting Paired Comparison Models in R. (http://epub.wu-wien.ac.at/dyn/openURL?id=oai:epub.wu-wien.ac.at:epub-wu-01_709)

Examples

## fit basic model casewise
data(cemspc)
mfr<-llbt.design(cemspc,nitems=6,objnames=c("lo","pa","mi","sg","ba","st"),
       blnCasewise=TRUE)
mm<-model.matrix(~lo+pa+mi+sg+ba+g1,data=mfr)
X<-mm[,-1]
p<-ncol(X)
ncat<-3
q<-length(levels(mfr$mu))*length(levels(mfr$CASE))
llbt.fit(mfr$y,X,q,ncat)

## fit the (aggregated) model with one subject covariate

data(cemspc)
mfr<-llbt.design(cemspc,nitems=6,objnames=c("lo","pa","mi","sg","ba","st")
      ,cov.sel="ENG")
eng<-mfr$ENG
eng<-factor(eng)
mm<-model.matrix(~lo+pa+mi+sg+ba+g1+(lo+pa+mi+sg+ba):eng,data=mfr)
X<-mm[,-1]
q<-length(levels(mfr$mu))*length(levels(eng))
ncat<-3
llbt.fit(mfr$y,X,q,ncat)

[Package prefmod version 0.8-13 Index]