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GLDISPLAY procedure

Displays further output from a GLMM analysis (R.W. Payne).


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


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.
The default is PRINT= mode, comp, effe, mean, back, moni, vcov, cova.
The deviance represents the variation remaining after fitting the fixed terms and all the random terms. It thus assesses how well those terms explain the random variation in the data.

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).

Parameters: none.

See also


Commands for: Regression analysis.


          !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]
Updated on February 7, 2023

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