Overview (GENLINMIXED command)
The GENLINMIXED procedure fits generalized linear mixed models. Generalized linear mixed models extend the linear model so that:
- The target is linearly related to the factors and covariates via a specified link function
- The target can have a non-normal distribution
- The observations can be correlated.
Generalized linear mixed models cover a wide variety of models, from simple linear regression to complex multilevel models for non-normal longitudinal data.
Probability Distribution of Target. The probability distribution of the target can be specified as normal, binomial, gamma, inverse Gaussian, multinomial, negative binomial, or Poisson.
Events/Trials Target Specification. The typical target specification will be a single field, but for the binomial distribution the target can be specified using a number-of-events field and a number-of-trials field. Alternatively, if the number of trials is the same across all subjects, then trials can be specified using a fixed number instead of a field.
Link Function. The target is linearly related to the model effects via one of the following link functions: Identity, complementary log-log, log, log-complement, logit, negative log-log, power, and probit.
Repeated Measurements. You can specify the subject structure for repeated measurements and how the errors of the repeated measurements are correlated. Complete independence is assumed across subject blocks.
Random Effects. Random-effects are effects whose values in the data file can be considered a random sample from a larger population of values. They are useful for explaining excess variability in the target.
Estimated Marginal Means. Estimated marginal means can be computed for one or more crossed factors and can be based on either the response or the linear predictor.
Output. The procedure produces a model viewer object containing tables and charts for assessing the quality of the model; also you can save predicted values to the active dataset and the model to a file in PMML format.
The basic specification is the GENLINMIXED command and the FIELDS subcommand with the TARGET keyword. This fits an intercept-only model that can be used as a basis for comparing more complicated models.
Note: Since measurement level can affect the results, if any variables (fields) have an unknown measurement level, an initial data pass will be performed to determine default measurement level for any variables with an unknown measurement level. For information on the criteria used to determine default measurement level, see SET SCALEMIN.
- The FIELDS subcommand is required. All other subcommands are optional.
- Subcommands can be specified in any order.
- There can be multiple RANDOM and EMMEANS subcommands; each RANDOM subcommand defines a separate random effects block, while each EMMEANS subcommand defines a separate set of estimated means. Only a single instance of any other subcommand is allowed.
- An error occurs if a keyword is specified more than once within a subcommand.
- Parentheses, equals signs, and slashes shown in the syntax chart are required.
- The command name, subcommand names, and keywords must be spelled in full.
- Empty subcommands are not allowed.
- Any split field defined on the SPLIT FILE command cannot be used on this command.
- Any field specifed on the WEIGHT command cannot be used on this command.
- The SPLIT FILE setting is ignored with a warning by the procedure.