15.9 GLM

GLM dependent_vars BY fixed_factors
     [/METHOD = SSTYPE(type)]
     [/DESIGN = interaction_0 [interaction_1 [... interaction_n]]]

The GLM procedure can be used for fixed effects factorial Anova.

The dependent_vars are the variables to be analysed. You may analyse several variables in the same command in which case they should all appear before the BY keyword.

The fixed_factors list must be one or more categorical variables. Normally it does not make sense to enter a scalar variable in the fixed_factors and doing so may cause PSPP to do a lot of unnecessary processing.

The METHOD subcommand is used to change the method for producing the sums of squares. Available values of type are 1, 2 and 3. The default is type 3.

You may specify a custom design using the DESIGN subcommand. The design comprises a list of interactions where each interaction is a list of variables separated by a ‘*’. For example the command

GLM subject BY sex age_group race
    /DESIGN = age_group sex group age_group*sex age_group*race

specifies the model subject = age_group + sex + race + age_group*sex + age_group*race. If no DESIGN subcommand is specified, then the default is all possible combinations of the fixed factors. That is to say

GLM subject BY sex age_group race

implies the model subject = age_group + sex + race + age_group*sex + age_group*race + sex*race + age_group*sex*race.

The MISSING subcommand determines the handling of missing variables. If INCLUDE is set then, for the purposes of GLM analysis, only system-missing values are considered to be missing; user-missing values are not regarded as missing. If EXCLUDE is set, which is the default, then user-missing values are considered to be missing as well as system-missing values. A case for which any dependent variable or any factor variable has a missing value is excluded from the analysis.