Automatic Model Fitting
When analyzing four-way or higher tables, finding the best fitting model can become increasingly difficult. Log-Linear Analysis contains automatic model fitting options to facilitate the search for a good model that fits the data. The general logic of this algorithm is as follows.
First, Statistica will fit a model with no relationships between factors; if that model does not fit (such as the respective Chi-square statistic is significant), it will fit a model with all two-way interactions. If that model does not fit either, Statistica will fit all three-way interactions, and so on.
Let's assume that this process found the model with all two-way interactions to fit the data. Statistica will then proceed to eliminate all two-way interactions that are not statistically significant. The resulting model will be the one that includes the least number of interactions necessary to fit the observed table.