GLM procedure

PROC GLM is a procedure that uses the least squares method to fit general linear models. GLM can be used to perform regression, analysis of variance, analysis of covariance, multivariate analysis of variance, and more.

Syntax

PROC GLM < options >;
  CLASS var(s);
  MODEL dependent = independents < / options >;
  BY var(s);
  CONTRAST "label" effect values < ... effect values > < / options >;
  ESTIMATE "label" effect values < ... effect values > < / options >;
  LSMEANS effects < / options >;
  MEANS effects < / options >;
  OUTPUT < OUT=SASdataset > keyword=names < ... > < / options >;
  RANDOM effects < /options >;
  REPEATED factor-specification < /options >;
  TEST < H=effects > E=effect < /options >;

RUN; QUIT;

The MODEL statement is required when using PROC GLM and only one model can be specified for a single procedure. If any variables or effects in the model are classification effects (categorical, dummy, etc), specify them on the CLASS statement. The CONTRAST and ESTIMATE statements allow you to test and make estimates of specific contrasts of interests. The values of an effect are listed in the order of that effect.