Analysing 2-factor 2-level design as if it were 4 different treatment design
Hello! Just curious why we see different results in such cases. Here we have a classic 2-factor 2-level factorial design which we can analyze using Nominal regression/logistic regression. Analysis shows that only interaction is significant : However, if we transform this data as if there were 4 factors A1, B1, C (A1*B1), D (A0*B0), then we will see that main effects are significant.
How can we ...