Generalized Linear Models Response
In many cases, you can simply specify a dependent variable; however, variables that take only two values and responses that record events in trials require extra attention.
- Binary response. When the dependent variable takes only two values, you can specify the reference category for parameter estimation. A binary response variable can be string or numeric.
- Number of events occurring in a set of trials. When the response is a number of events occurring in a set of trials, the dependent variable contains the number of events and you can select an additional variable containing the number of trials. Alternatively, if the number of trials is the same across all subjects, then trials may be specified using a fixed value. The number of trials should be greater than or equal to the number of events for each case. Events should be non-negative integers, and trials should be positive integers.
For ordinal multinomial models, you can specify the category order of the response: ascending, descending, or data (data order means that the first value encountered in the data defines the first category, the last value encountered defines the last category).
Scale Weight. The scale parameter is an estimated model parameter related to the variance of the response. The scale weights are "known" values that can vary from observation to observation. If the scale weight variable is specified, the scale parameter, which is related to the variance of the response, is divided by it for each observation. Cases with scale weight values that are less than or equal to 0 or are missing are not used in the analysis.
How To Select Predictors for Generalized Linear Models
This feature requires the Advanced Statistics option.
- From the menus choose:
- In the Generalized Linear Models dialog box, click Predictors.