The GENMOD Procedure

ODS Graphics

ODS Graph Names

Statistical procedures use ODS Graphics to create graphs as part of their output. ODS Graphics is described in detail in Chapter 21: Statistical Graphics Using ODS.

Before you create graphs, ODS Graphics must be enabled (for example, by specifying the ODS GRAPHICS ON statement). For more information about enabling and disabling ODS Graphics, see the section Enabling and Disabling ODS Graphics in Chapter 21: Statistical Graphics Using ODS.

The overall appearance of graphs is controlled by ODS styles. Styles and other aspects of using ODS Graphics are discussed in the section A Primer on ODS Statistical Graphics in Chapter 21: Statistical Graphics Using ODS.

Some graphs are produced by default; other graphs are produced by using statements and options. You can reference every graph produced through ODS Graphics with a name. The names of the graphs that PROC GENMOD generates are listed in Table 40.15, along with the required statements and options.

ODS Graph Names

PROC GENMOD assigns a name to each graph it creates using ODS. You can use these names to reference the graphs when using ODS. The names are listed in Table 40.15.

To request these graphs, ODS Graphics must be enabled and you must specify the statement and options indicated in Table 40.15.

Table 40.15: Graphs Produced by PROC GENMOD

ODS Graph Name	Description	Statement	Option
ADPanel	Autocorrelation function and density panel	BAYES	PLOTS=(AUTOCORR DENSITY)
AutocorrPanel	Autocorrelation function panel	BAYES	PLOTS= AUTOCORR
AutocorrPlot	Autocorrelation function plot	BAYES	PLOTS(UNPACK)=AUTOCORR
ClusterCooksDPlot	Cluster Cook’s D by cluster number	PROC	PLOTS=
ClusterDFFITPlot	Cluster DFFIT by cluster number	PROC	PLOTS=
ClusterLeveragePlot	Cluster leverage by cluster number	PROC	PLOTS=
CooksDPlot	Cook’s distance	PROC	PLOTS=
CumResidPanel	Panel of aggregates of residuals	ASSESS	CRPANEL
CumulativeResiduals	Model assessment based on aggregates of residuals	ASSESS	Default
DevianceResidByXBeta	Deviance residuals by linear predictor	PROC	PLOTS=
DevianceResidualPlot	Deviance values	PROC	PLOTS=
DFBETAByCluster	Cluster DFBeta by cluster number	PROC	PLOTS=
DFBETAPlot	DFBeta	PROC	PLOTS=
DiagnosticPlot	Panel of residuals, influence, and diagnostic statistics	PROC MODEL REPEATED	PLOTS=
LeveragePlot	Leverage	PROC	PLOTS=
LikeResidByXBeta	Likelihood residuals by linear predictor	PROC	PLOTS=
LikeResidualPlot	Likelihood residuals	PROC	PLOTS=
PearsonResidByXBeta	Pearson residuals by linear predictor	PROC	PLOTS=
PearsonResidualPlot	Pearson residuals	PROC	PLOTS=
PredictedByObservation	Predicted values	PROC	PLOTS=
RawResidByXBeta	Raw residuals by linear predictor	PROC	PLOTS=
RawResidualPlot	Raw residuals	PROC	PLOTS=
StdDevianceResidByXBeta	Standardized deviance residuals by linear predictor	PROC	PLOTS=
StdDevianceResidualPlot	Standardized deviance residuals	PROC	PLOTS=
StdDFBETAByCluster	Standardized cluster DFBeta by cluster number	PROC	PLOTS=
StdDFBETAPlot	Standardized DFBeta	PROC	PLOTS=
StdPearsonResidByXBeta	Standardized Pearson residuals by linear predictor	PROC	PLOTS=
StdPearsonResidualPlot	Standardized Pearson residuals	PROC	PLOTS=
TAPanel	Trace and autocorrelation function panel	BAYES	PLOTS=(TRACE AUTOCORR)
TADPanel	Trace, autocorrelation, and density function panel	BAYES	Default
TDPanel	Trace and density panel	BAYES	PLOTS=(TRACE DENSITY)
TracePanel	Trace panel	BAYES	PLOTS=TRACE
TracePlot	Trace plot	BAYES	PLOTS(UNPACK)=TRACE
ZeroInflationProbPlot	Zero-inflation probabilities	PROC	PLOTS=