Selects information to be printed by the analysis and controls certain aspects of the method used.
This specifies which items of output are to be produced by the analysis.
|Model||Description of the model fitted by the analysis|
|Variance components||Estimates of variance parameters|
|Estimated effects||Estimates of regression coefficients|
|Predicted means||Predicted means|
|Residual checks||Uses the VCHECK procedure to check the residuals for outliers and variance stability|
|Covariance model||Estimated covariance models in matrix format|
|Variance-covariance matrix||Variance-covariance matrix for the variance parameters|
|Deviance||The residual deviance|
|Wald tests||Wald tests for fixed model terms and accompanying F-statistics (if selected)|
|Missing value estimates||Estimates of values missing from the input|
|Monitoring||Monitoring information at each iteration|
|Akaike information coefficient (AIC)||Akaike information coefficient to assess the random model|
|Schwarz information coefficient (SIC)||Schwarz information coefficient to assess the random model|
Tables of means and effects are accompanied by estimates of standard errors. You can choose whether Genstat computes standard errors or standard errors of differences (SEDs) for the tables.
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).|
Covariates centred to zero mean
Specifies whether covariates are centred to zero mean during the analysis. This applies to all covariates in the model. If covariates are centred, tables of predicted means are based on the mean covariate value, otherwise zero for each covariate.
Constrain variance components to be positive
This specifies whether the variance components are constrained to be positive.
- Multivariate Linear Mixed Models menu.
- Further Output for obtaining additional output after fitting a model.
- Save for saving the results from a REML analysis.
- REML directive for command mode use of REML, with additional options to control the algorithm and for more sophisticated analyses.
- Reml Predictions menu for forming predictions.
- VCHECK procedure to check the residuals.