plot.mlcm.df: Create Conjoint Proportion Plot from mlcm.df Object

In MLCM: Maximum Likelihood Conjoint Measurement

Create Conjoint Proportion Plot from mlcm.df Object

Description

Creates a conjoint proportions plot as in Ho et al. (2008) in which the proportion of responses of one type are indicated as a function of the stimulus pairs used in the experiment.

Usage

## S3 method for class 'mlcm.df'
plot(x, clr = NULL, ...)

Arguments

x	object of class ‘mlcm.df’ typically the result of a conjoint measurement experiment of 2 dimensions.
clr	a palette for the color scale in the plot. If none specified, then a grey level palette will be calculated based on the maximum number of repetitions.
...	additional graphical parameters passed to image used for generating the plot.

Details

The input should be a data frame of class ‘mlcm.df’ that contains 5 columns. The first column contains the responses of the observer. The next two correspond to the indices of the stimuli along the first dimensions and the last two the indices of the two stimuli along the second dimension. The plot shows a color-coded (grey-level by default) map of the proportion of responses for each combination of indices in one stimulus with respect to the combinations of the indices in the other. There should be several replications of each pairing for the plot to make some sense.

Value

Currently, nothing is returned. Used for its side-effect of producing a plot.

Note

Will not work on experiments using more than 2 dimensions.

Author(s)

Ken 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

image

Examples

	data(BumpyGlossy)
	plot(BumpyGlossy, 
		xlab = expression(paste("Surface ", S[ij], 
		" Gloss Level (i) and Bump level (j)")),
		ylab = expression(paste("Surface ", S[kl], 
		" Gloss Level (k) and Bump level (l)")) 
	)

MLCM documentation built on March 18, 2022, 7:31 p.m.