anova.mlcm {MLCM}

Analysis of Deviance for Maximum Likelihood Conjoint Measurement Model Fits

Description

Compute an analysis of deviance table for one or more maximum likelihood conjoint measurement model fits.

Usage

## S3 method for class 'mlcm'
anova(object, ..., dispersion = NULL, test = NULL)

Arguments

object, ...

objects of class mlcm, typically the result of a call to mlcm

dispersion

the dispersion parameter for the fitting family. By default, it is obtained from the object(s)

test

a character string (partially) matching one of "Chisq", "F", or "Cp". See stat.anova. Normally, "Chisq" is the appropriate value, here.

Details

See anova.glm for details. In brief, specifying a single object, results in the display of a sequential analysis of deviance table for that model. Specifying several objects, a table indicating the results of the likelihood ratio tests between successive models is displayed. The models must be nested and fit to the same data set. One can mix a formula method model with a glm model, but not more than one comparison between a pair of such models at a time.

Value

An object of class "anova" inheriting from class "data.frame".

Warning

see section Warnings in anova for warnings.

Author(s)

Kenneth Knoblauch

References

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

anova.glm, anova, glm

Examples

bg.add <- mlcm(BumpyGlossy)
bg.ind <- mlcm(BumpyGlossy, model = "ind", whichdim = 2)
bg.full <- mlcm(BumpyGlossy, model = "full")

anova(bg.ind, bg.add, bg.full, test = "Chisq")