Displays further output from a `GLMM`

analysis (R.W. Payne).

### Options

`PRINT` = string token |
What output to display (`model` , `components` , `effects` ,` fittedvalues` , `means` , `backmeans` , `vcovariance` ,` waldtests` , `missingvalues` , `covariancemodels` , `deviance` ); default * |

`PTERMS` = formula |
Formula specifying fixed terms for which means or back-transformed means are to be printed; default * prints all the fixed model terms |

`PSE` = string token |
Standard errors to print with tables of means (`se` ,` sesummary` , `sed` , `sedsummary` , `vcovariance` , `differences` ,` estimates` , `alldifferences` , `allestimates` ); default `seds` |

`OFFSET` = scalar |
Offset value to use when calculating predicted means; default 0 |

`RMETHOD` = string token |
Which random terms to use when calculating `RESIDUALS` (`final` , `all` ); default `fina` |

`CFORMAT` = string token |
Whether printed output for covariance models gives the variance matrices or the parameters (`variancematrices` , `parameters` ); default `vari` |

`FMETHOD` = string token |
Controls whether and how to calculate F-statistics for fixed terms (`automatic` , `none` , `algebraic` , `numerical` ); default `auto` |

`GLSAVE` = pointer |
Save structure from the `GLMM` analysis |

### No parameters

### Description

`GLDISPLAY`

allows you to display further output from a `GLMM`

analysis. By default the output is from the most recent `GLMM`

analysis. Alternatively, you can set the `GLSAVE`

parameter to a save structure (saved using the `GLSAVE`

parameter of `GLMM`

) to obtain output from an earlier analysis.

The `PRINT`

option selects the output to be displayed:

`model`

description of model fitted,`components`

estimates of variance components and estimated parameters of `covariance`

models, `effects`

estimates of parameters *α*and

*β*, the fixed and random effects,

`fittedvalues`

table containing the y-variate, fitted values, residuals on the natural scale and standardized residuals on the scale of the linear predictor,`means`

predicted means for factor combinations,`backmeans`

back-transformed means,`vcovariance`

variance-covariance matrix of the estimated components,`waldtests`

Wald tests for fixed terms,`missingvalue`

estimates of missing values,`covariancemodels`

estimated covariance models and deviance from the generalized linear model.`PRINT= mode`

, `comp`

, `effe`

, `mean`

, `back`

, `moni`

,` vcov`

, `cova`

.The `RMETHOD`

option controls the way in which residuals and fitted values are formed. With the default setting `RMETHOD=final`

, the fitted values are calculated from all the fixed and random effects. The setting `RMETHOD=all`

can be used to obtain fitted values constructed from the fixed terms alone, omitting all random terms. (The residuals are then calculated as the differences between the values of the y-variate and the fitted values.) To avoid problems with 0 and 100% observations, the standardized residuals on the linear-predictor scale are calculated as differences between the adjusted dependent variate and the fitted values on that scale (and then standardized by their standard errors).

The `PTERMS`

option can specify which tables of means are printed; by default, tables of means are produced for all the terms in the fixed model.

The `PSE`

option controls the standard errors that are printed with tables of means and effects:

`se`

standard errors,`sesummary`

summary of the standard errors (default),`sed`

standard errors of differences between pairs of means,`sedsummary`

summary of the standard errors of differences,`vcovariance`

variance-covariance matrix for the means,`allestimates`

synonym of `se`

,`estimates`

synonym of `sesummary`

,`alldifferences`

synonym of `sed`

,`differences`

synonym of `sedsummary`

.The `OFFSET`

option specifies the offset value to use when calculating predicted means. The default is zero.

The `CFORMAT`

option controls the type of output produced for the estimated covariance models. The default setting, `variancematrices`

, produces the variance-covariance matrices for the components, whereas the setting `parameters`

prints their parameters.

The `FMETHOD`

option controls whether to accompany the Wald tests for fixed effects 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, with the default setting `FMETHOD=automatic`

, Genstat assesses the model itself and decides 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).Options: `PRINT`

, `PTERMS`

, `PSE`

, `OFFSET`

, `RMETHOD`

, `CFORMAT`

, `FMETHOD`

, `GLSAVE`

.

Parameters: none.

### See also

Procedures: `GLMM`

, `GLKEEP`

, `GLPERMTEST`

, `GLPLOT`

, `GLPREDICT`

, `GLRTEST`

, `GLTOBITPOISSON`

.

Commands for: Regression analysis.

### Example

CAPTION 'GLDISPLAY example',\ !t('Data from an experiment on Great Knott, Rothamsted;',\ 'see West, J.S., Fitt, B.D.L., Leech, P.K., Biddulph, J.E.,',\ 'Huang, Y.-J. &, Balesdent, M.-H. (2002).',\ 'Effects of timing of ~italic{Leptosphaeria maculans}',\ 'ascospore release and fungicide regime on phoma leaf spot',\ 'and phoma stem canker development on winter oilseed rape',\ '(~italic{Brassica napus}) in southern England.',\ 'Plant Pathology, 51, 454–463.'); STYLE=meta,plain SPLOAD [PRINT=*] '%data%/GtKnott2000.gsh' GLMM [PRINT=model,components,wald; DISTRIBUTION=binomial; LINK=logit;\ DISPERSION=*; FIXED=Cultivar*Fungicide; RANDOM=Block/Wholeplot;\ FMETHOD=all] LMplants; NBINOMIAL=Nplants GLDISPLAY [PRINT=means,backmeans,deviance; DEVMETHOD=fulllikelihood]