GLM dependent_vars BY fixed_factors
[/METHOD = SSTYPE(type)]
[/DESIGN = interaction_0 [interaction_1 [... interaction_n]]]
[/INTERCEPT = {INCLUDE|EXCLUDE}]
[/MISSING = {INCLUDE|EXCLUDE}]
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.