Use this to select different options to be used in screening tests for Generalized Linear Models.
Specifies which items of output are to be displayed in the Output window.
|Model||Description of the model|
|Tests||Marginal and conditional test statistics|
|Pooled||Accumulated analysis of variance or deviance in which terms with the same number of identifiers, e.g. main effects or two-factor interactions, are pooled|
|P-value||(approximate) P-values from F-tests|
|Star scheme||Significance of P-values by a conventional star notation|
Estimate constant term
Specifies whether to include a constant in the model.
Exclude higher order interaction terms
Controls whether to exclude higher-order interactions in the conditional regression model for each tested term.
Controls which warning messages to suppress when fitting the complete model. You can suppress those for aliasing or marginality. Note: warning messages are always suppressed when fitting models for individual tests.
A variate of weights can be supplied to give varying influence of each unit on the fit of the model.
Specifies a variate that can be used to take account of a fixed contribution to the linear effects for each unit, referred to as the offset.
Controls whether the dispersion parameter for the variance of the response is estimated from the residual mean square of the fitted model, or fixed at a given value. The dispersion parameter (fixed or estimated) is used when calculating standard errors and standardized residuals. In models with the binomial, Poisson, negative binomial, geometric and exponential distributions, the dispersion should be fixed at 1 unless a heterogeneity parameter is to be estimated.