Type I Sums of Squares
This option is selected by default. The sums of squares decomposition reflects the amount of variance each term contributes to the overall model variation.
The effects are balanced if all possible factor level combinations occur in the data the same number of time. If the effects are balanced, the predictors are orthogonal and the sums of squares decomposition does not depend on the order in which the predictors are specified in the formula. If the effects are unbalanced, each sum of squares reflects the variance contributed by that effect once the preceding effects in the formula have been accounted for. The order of the predictors in the formula does not affect the model fit, but does affect the ANOVA decomposition.
The F-statistic and p-value for each term test whether that term contributes significantly to the model. With unbalanced data, each F-statistic tests the value of including each term, given that the preceding terms are already in the model. With balanced data, each F-statistic tests the value of including each term, given that all other terms are included in the model.