Description Usage Source References Examples
These are results of a detergent brand preference study, with
respondents classified by temperature and softness used during their
wash cycle. Venables and Ripley call Brand
the response
factor and M.user
, Temp
and Soft
stimulus
factors. Thus they are most interested in Brand
and in
interactions that involve Brand
.
1 |
Ries and Smith (1963) The use of chi-square for preference testing in multidimensional problems. Chemical Engineering Progress 59, 39-43.
Venables and Ripley (1999) Modern Applied Statistics with S-PLUS, 2nd ed., ch. 7. (this is not in the 3rd ed) Cox and Snell (1989) Analysis of Binary Data, Chapman \& Hall.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # Four-way Contingency Table
data( BrandX )
# fit poisson model
BrandX.fit <- glm( Fr ~ M.user*Temp*Soft+Brand,
family = poisson, data = BrandX )
anova( BrandX.fit, test = "Chisq" )
drop1( BrandX.fit, formula( BrandX.fit), test = "Chisq" )
BrandX.step <- step(BrandX.fit,
list( lower = formula( BrandX.fit ), upper = ~.^3 ),
scale = 1, trace = FALSE)
BrandX.step$anova
anova( BrandX.step, test = "Chisq" )
BrandX.mod <- glm( terms( Fr ~ M.user*Temp*Soft +
Brand*M.user*Temp, keep.order = TRUE ),
family = poisson, data = BrandX )
summary(BrandX.mod, correlation = FALSE, test = "Chisq" )
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