SPSS® 12.0 Command Syntax Reference

UNIANOVA 1621
• To include the intercept term in the design, use the keyword INTERCEPT on the DESIGN
subcommand. If INTERCEPT is specified on the DESIGN subcommand, the subcommand
INTERCEPT=EXCLUDE is overridden.
• To include a term for an interaction between factors, use the keyword BY or the asterisk
(*) to join the factors involved in the interaction. For example, A*B means a two-way
interaction effect of A and B, where A and B are factors. A*A is not allowed because factors
inside an interaction effect must be distinct.
• To include a term for nesting one effect within another, use the keyword WITHIN or a pair
of parentheses on the DESIGN subcommand. For example, A(B) means that A is nested
within B. The expression A(B) is equivalent to the expression A WITHIN B. When more than
one pair of parentheses is present, each pair of parentheses must be enclosed or nested
within another pair of parentheses. Thus, A(B)(C) is not valid.
• Multiple nesting is allowed. For example, A(B(C)) means that B is nested within C, and A
is nested within B(C).
• Interactions between nested effects are not valid. For example, neither A(C)*B(C) nor
A(C)*B(D) is valid.
• To include a covariate term in the design, enter the name of the covariate on the DESIGN
subcommand.
• Covariates can be connected, but not nested, through the * operator to form another covariate
effect. Therefore, interactions among covariates such as X1*X1 and X1*X2 are valid,
but not X1(X2). Using covariate effects such as X1*X1, X1*X1*X1, X1*X2, and X1*X1*X2*X2
makes fitting a polynomial regression model easy in UNIANOVA.
• Factor and covariate effects can be connected only by the * operator. Suppose A and B are
factors, and X1 and X2 are covariates. Examples of valid factor-by-covariate interaction
effects are A*X1, A*B*X1, X1*A(B), A*X1*X1, and B*X1*X2.
• If more than one DESIGN subcommand is specified, only the last one is in effect.
Example
UNIANOVA Y BY A B C WITH X
/DESIGN A B(A) X*A.
• In this example, the design consists of a main effect A, a nested effect B within A, and an
interaction effect of a covariate X with a factor A.