| Detergent | R Documentation |
Detergent preference data
Description
Cross-classification of a sample of 1008 consumers according to (a) the softness of the laundry water used, (b) previous use of detergent Brand M, (c) the temperature of laundry water used and (d) expressed preference for Brand X or Brand M in a blind trial.
Usage
data(Detergent)
Format
A 4-dimensional array resulting from cross-tabulating 4 variables for 1008 observations. The variable names and their levels are:
| No | Name | Levels |
| 1 | Temperature | "High", "Low" |
| 2 | M_User | "Yes", "No" |
| 3 | Preference | "Brand X", "Brand M" |
| 4 | Water_softness | "Soft", "Medium", "Hard" |
Source
Fienberg, S. E. (1980). The Analysis of Cross-Classified Categorical Data Cambridge, MA: MIT Press, p. 71.
References
Ries, P. N. & Smith, H. (1963). The use of chi-square for preference testing in multidimensional problems. Chemical Engineering Progress, 59, 39-43.
Examples
data(Detergent)
# basic mosaic plot
mosaic(Detergent, shade=TRUE)
require(MASS)
(det.mod0 <- loglm(~ Preference + Temperature + M_User + Water_softness,
data=Detergent))
# examine addition of two-way terms
add1(det.mod0, ~ .^2, test="Chisq")
# model for Preference as a response
(det.mod1 <- loglm(~ Preference + (Temperature * M_User * Water_softness),
data=Detergent))
mosaic(det.mod0)