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For the multivariate analysis of binary (or n-ary) dependent variables, common statistical analysis systems offer models with non-homogeneous error variance (LSN-models), and optionally transformations (“response functions”) of the relative frequencies, above all the logit function. Using the simplest possible example—two groups with a relative frequency in each—it is shown that significance tests...
The standard model for the analysis of variance with random effects implies, for the case of two independent variables, that single effects must be tested not against the error, but against the interaction mean squares. This causes, in comparison with the fixed effects AV, a considerable loss of test power, particularly for the 2 × 2 table. An alternative modelling of the interaction effect is proposed...
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