MLCM-package {MLCM}R Documentation

Maximum Likelihood Conjoint Measurement

Description

Estimate perceptual scales from data collected in a conjoint measurement experiment by maximum likelihood. Data for conjoint measurement are typically collected using a psychophysical procedure. The stimuli vary along n >= 2 dimensions. The observer views pairs of stimuli and judges which stimulus of each pair is higher on a specified dimension. For example, stimuli may be goods baskets containing amounts of milk and honey (dimensions) and the subject may order each pair of baskets by subjective desirability. This package contains functions to estimate the additive contribution of the n scales to the judgment by a maximum likelihood method under several hypotheses of how the perceptual dimensions interact.

Details

Package: MLCM
Type: Package
Version: 0.0-1
Date: 2009-08-17
License: GPL
LazyLoad: yes
LazyData: yes
Built: R 2.9.1; ; 2009-08-17 13:38:05 UTC; unix

Index:

BumpyGlossy     Conjoint Measurement Data for Bumpiness and
        Glossiness
MLCM-package    Estimate perceptual scales from a conjoint
        measurement experiment by maximum likelihood
anova.mlcm      Likelihood ratio tests for Maximum Likelihood 
        Conjoint Measurement models
logLik.mlcm     Calculate log likelihood for Conjoint Measurement models
make.wide       Create data frame for Fitting Conjoint Measurment 
    Scale by glm
mlcm    Fit Conjoint Measurement Models by Maximum
        Likelihood
plot.mlcm       plot method for Maximum Likelihood Conjoint Measurement 
    models
print.mlcm      print method for Maximum Likelihood Conjoint
        Measurement models
print.summary.mlcm      print  method for summary of Maximum 
    Likelihood Conjoint Measurement models
summary.mlcm    summary method for Maximum Likelihood Conjoint 
    Measurement models

Author(s)

Kenneth Knoblauch

Maintainer: Ken Knoblauch <ken.knoblauch@inserm.fr>

References

Luce, R. D., and Tukey, J. W. (1964). Simultaneous conjoint measurement. Journal of Mathematical Psychology, 1, 1–27.

Krantz, D. H., Luce, R. D., Suppes, P., and Tversky, A. (1971). Foundations of Measurement, Vol. 1: Additive and Polynomial Representations. New York: Academic Press.

Ho, Y. H., Landy. M. S. and Maloney, L. T. (2008). Conjoint measurement of gloss and surface texture. Psychological Science, 19, 196–204.

See Also

glm

Examples

bg.acm <- mlcm(BumpyGlossy)
plot(bg.acm, pch = 21:22, bg = c("blue", "red"), col = "black",
        ylab = "Contributions to Perceived Bumpiness")

[Package MLCM version 0.0-6 Index]