User Guide

48
Chapter 4

A polynomial regression model in which any lower-order terms are specified
before any higher-order terms.
 A purely nested model in which the first-specified effect is nested within the
second-specified effect, the second-specified effect is nested within the third, and
so on. (This form of nesting can be specified only by using syntax.)
Type III. The default. This method calculates the sums of squares of an effect in the
design as the sums of squares adjusted for any other effects that do not contain it and
orthogonal to any effects (if any) that contain it. The Type III sums of squares have one
major advantage in that they are invariant with respect to the cell frequencies as long
as the general form of estimability remains constant. Hence, this type of sums of
squares is often considered useful for an unbalanced model with no missing cells. In a
factorial design with no missing cells, this method is equivalent to the Yates’ weighted-
squares-of-means technique. The Type III sum-of-squares method is commonly used
for:
 Any models listed in Type I.
 Any balanced or unbalanced model with no empty cells.