29
Jun
Type Iii Sum Of Squares. Any balanced or unbalanced model with no empty cells. Type I sum of squares are sequential In essence the factors are tested in the order they are listed in the model. Input y batch time. I think it is sumpredicted y of the full model - predicted y of the reduced model2.
This method is designed for a situation in which there are missing cells. And now I have Type III sums of squares for A B and their interaction AB using drop1model testF. In non-orthogonal factorial between-subjects designs that typically result from non-proportional unequal cell sizes so-called type I-III sums of squares SS can give different results in an ANOVA for all tests but the highest interaction effect. Cells Type III sums of squares generally do not test hypotheses about least squares means but instead test hypotheses that are complex functions of the patterns of missing cells in higher-order containing interactions and that are ordinarily not meaningful. Type III Sum of Squares aka Partial Type III SS is the SS corresponding to each effect adjusted for every other effect in the model. I apologize that this is not really a SAS question.
Type I sum of squares are sequential In essence the factors are tested in the order they are listed in the model.
However the last of the Type III tests will always equal the last of the Type I tests. For any effect F in the design if F is not. For ANOVA designs with unequal ns however Type III sums of squares test the same hypothesis that would be tested if the cell ns were equal. 10 A 1 10 A 2 30 A 3 10 B 1 20 B 2 10 B 3. Re-read the hypotheses being tested to see that this is so. Cells Type III sums of squares generally do not test hypotheses about least squares means but instead test hypotheses that are complex functions of the patterns of missing cells in higher-order containing interactions and that are ordinarily not meaningful.