Rafael,
when testing binomial hypotheses with both repeated measures and
inter-group factors, you should make explicit your model on the
intra-subject part of the data. You can't do Chi-square comparisons on
count data that mix independent and dependent measures.
But you can define a Bernoulli logistic model at the individual single
response level, and define a proper subject factor, and a stimulus-type
factor, and possibly an item factor (nested within the stimulus-type
category). This may be viewed as a Rasch model of measurement.
Within this model, coefficient estimates on the subject factor are
measures of individual ability that can be a posteriori introduced in an
ANOVA.
In some cases, you can model the intra-subject part of the data as a
temporal model, assuming for instance that subjects are getting more
efficient as time goes on.
HTH,
Yvonnick.
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