1. Home
2. Generalized Linear Mixed Model Further Output

# Generalized Linear Mixed Model Further Output

Use this to select further output following fitting a Generalized Linear Mixed Model. ## Display

This specifies which items of output are to be displayed.

 Model Description of the model fitted by the analysis Variance components Estimates of variance parameters Fitted values The fitted values and residuals from the model Estimated effects Estimates of regression coefficients Predicted means Predicted means Back transformed means Back transformed means Variance-covariance matrix Variance-covariance matrix for the variance parameters Missing value estimates Estimates of missing values Wald tests Wald Tests for fixed model terms and accompanying F-statistics Deviance The residual deviance and information selected below Covariance model Estimated covariance models in the selected format (Variance matrix or Parameters)

## Standard errors

This specifies which standard errors are to be displayed with the tables of means.

 Differences Summary of standard errors of differences between means Estimates Summary of standard errors of means All Differences Full matrix of standard errors between means All Estimates Full table of standard errors of means Variance-covariance Variance-covariance matrix for the table

## Method for calculating F-statistics

This controls whether Wald tests for fixed effects are accompanied with approximate F statistics and corresponding numbers of residual degrees of freedom. The computations, using the method devised by Kenward & Roger (1997), can be time consuming with large or complicated models. So, the default setting automatic, can be used to allow Genstat to assess the model itself and decide automatically whether to do the computations and which method to use. The other settings allow you to control what to do yourself:

 none No F statistics are produced algebraic F statistics are calculated using algebraic derivatives (which may involve large matrix calculations) numerical F statistics are calculated using numerical derivatives (which require an extra evaluation of the mixed model equations for every variance parameter).

## Offset for predicted means

Value of offset to use when calculating the means and back-transformed means; if this is not set a default value of 0 will be used.

## Model terms for effects and means

This specifies the model terms, as a formula, for which tables of means and/or effects are displayed. For covariates, the associated linear regression parameter can be printed as an effect, but predicted means are not available. Predicted means for other terms are adjusted to the mean of the covariate (but see note below). The formula can include the string ‘Constant’ to include entries for the constant term.

If no formula is specified, means or effects are produced for all the fixed model terms and none of the random terms.

## Graphics

The Residual plots button can be used to generate plots of residuals.
The Means plot button can be used to generate plots of the means.
The Separation plot button can be used to generate a plot of the observed versus the fitted probabilities in a separation plot.

## Permutation tests

The Permutation test button can be used to run a permutation test, using the GLPERMTEST procedure, to assess the significance of the fixed terms.

## Likelihood test for random terms

The Likelihood test for random terms button can be used to run a permutation test,
using the GLRTEST procedure, to assess the significance of the random terms.

## Action Icons Pin Controls whether to keep the dialog open when you click Run. When the pin is up the dialog will remain open, otherwise when the pin is down the dialog will close. Clear Clear all fields and list boxes. Help Open the Help topic for this dialog.