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MLCM (version 0.0-3)

Maximum Likelihood Conjoint Measurement

Description

Conjoint measurement is a psychophysical procedure in which stimulus pairs are presented that vary along 2 or more dimensions and the observer is required to compare the stimuli along one of them. This package contains functions to estimate the contribution of the n scales to the judgment by a maximum likelihood method under several hypotheses of how the perceptual dimensions interact.

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Version

Install

install.packages('MLCM')

Monthly Downloads

309

Version

0.0-3

License

GPL

Maintainer

Ken Knoblauch

Last Published

September 22nd, 2009

Functions in MLCM (0.0-3)

plot.mlcm

Plot an mlcm Object
anova.mlcm

Analysis of Deviance for Maximum Likelihood Conjoint Measurement Model Fits
boot.mlcm

Resampling of an Estimated Conjoint Measurement Scale
fitted.mlcm

Fitted Responses for a Conjoint Measurement Scale
mlcm

Fit Conjoint Measurement Models by Maximum Likelihood
plot.mlcm.df

Create Conjoint Proportion Plot from mlcm.df Object
logLik.mlcm

Extract Log-Likelihood from mlcm Object
binom.diagnostics

Diagnostics for Binary GLM
summary.mlcm

Summary Method for mlcm objects
MLCM-package

Maximum Likelihood Conjoint Measurement
make.wide

Create data frame for Fitting Conjoint Measurment Models by glm
BumpyGlossy

Conjoint Measurement Data for Bumpiness and Glossiness