llbt.fit: Function to fit an LLBT

In prefmod: Utilities to Fit Paired Comparison Models for Preferences

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	maximum number of iterations (default 100)

Details

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

Author(s)

Reinhold Hatzinger

References

Hatzinger, R., & Francis, B. (2004). Fitting paired comparison models in R. https://epub.wu.ac.at/id/eprint/740

Examples

# fit basic model casewise
mfr <- llbt.design(cemspc, nitems = 6,
    objnames = c("lo", "pa", "mi", "sg", "ba", "st"),
    casewise = 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
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)

prefmod documentation built on June 11, 2022, 3 p.m.