GLM Options

Select the output to be generated initially in a GLM analysis - the same information can also be displayed after the analysis, using the Further Output menu.

Display

Model	details of the model that is fitted
Summary	summary analysis of deviance
F-probabilities	approximate F-probabilities for deviance ratios
Correlations	correlations between the parameter estimates
Estimates	estimates of the parameters in the model
t-probabilities	approximate t-probabilities for the parameter estimates
Fitted Values	table containing the values of the response variate, fitted values, standardized residuals and leverages
Accumulated	analysis-of-deviance table containing a line for each change in the fitted model

Dispersion Parameter

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.

Estimate Constant Term

Specifies whether to include a constant in the model. In models with no factors as explanatory variates, this omits the intercept; in other words the fitted line is constrained to pass through the origin. If a factor is included, the omission of a constant leads to a re-parameterization of the same model.

Fit Model Terms Individually

If selected, regression models will be fitted one term at a time. If the accumulated display option is set then the accumulated summary will contain a line for each individual term in a model.

Offset

A generalized linear model can be modified to take account of a fixed contribution to the linear effects for each unit, supplied in a variate referred to as the offset.

Weights

A variate of weights can be supplied to give varying influence of each unit on the fit of the model. This would usually correspond to a known pattern of variance of the observations, when the weights would be the reciprocal of the variances.

Absorbing Factor

A factor can be supplied to specify an absorbing factor defining the groups for within-groups linear or generalized linear regression.

Level of Interaction

For a general GLM, you can control the maximum order of interaction to be generated when you use model-formula operators like *. The default is to include all interactions, up to those involving nine variates or factors. (You cannot ask for more than nine.)