# Sum of Squares (Variance Components)

For the model, you can choose a type of sum of squares. Type III is the most commonly used and is the default.

**Type I.** This method is also known as the hierarchical decomposition of the
sum-of-squares method. Each term is adjusted for only the term that
precedes it in the model. The Type I sum-of-squares method is commonly
used for:

- A balanced ANOVA model in which any main effects are specified before any first-order interaction effects, any first-order interaction effects are specified before any second-order interaction effects, and so on.
- 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. Therefore,
this type 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 models with no empty cells.