Model Selection

If the slopes’ p-value is significant (by default, less than 0.25), the separate intercepts, separate slopes model is used to estimate shelf life.

If the slopes’ p-value is not significant, Statistica determines if the intercepts are equal across different batches. If the intercepts’ p-value is significant (by default, less than 0.25), the separate intercepts, common slope model is used. If neither the slopes’ p-value nor the intercepts’ p-value are significant (by default, less than 0.25) the common intercept, common slope model is used.

The p-values are computed by using the type 1 sums of squares decomposition of the full linear model with effects placed into the model in the following order: time, batch, batch by time interaction. The slopes’ p-value is associated with the batch by time interaction and the intercepts’ p-value is associated with the batch effect.