Overview of Balanced ANOVA and GLM
overview     see also      

Balanced ANOVA and general linear model (GLM) are ANOVA procedures for analyzing data collected with many different experimental designs. Your choice between these procedures depends upon the experimental design and the available options. The experimental design refers to the selection of units or subjects to measure, the assignment of treatments to these units or subjects, and the sequence of measurements taken on the units or subjects. Both procedures can fit univariate models to balanced data with up to 31 factors. Here are some of the other options:

 

Balanced ANOVA

GLM

Can fit unbalanced data

no

yes

Can specify factors as random and obtain expected means squares

yes

yes

Fits covariates

no

yes

Performs multiple comparisons

no

yes

Fits restricted/unrestricted forms of mixed model

yes

unrestricted only

Stores a model for further analyses

no

yes

You can use balanced ANOVA to analyze data from balanced designs. See Balanced designs. You can use GLM to analyze data from any balanced design, though you cannot choose to fit the restricted case of the mixed model, which only balanced ANOVA can fit. See Restricted and unrestricted form of mixed models.

To classify your variables, determine if your factors are:

·    crossed or nested

·    fixed or random

·    covariates

For easy entering of repeated factor levels into your worksheet, see Using patterned data to set up factor levels.