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 43.15, along with the required statements and options.
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 43.15.
To request these graphs, ODS Graphics must be enabled and you must specify the statement and options indicated in Table 43.15.
Table 43.15: 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 
CRPANEL 

CumulativeResiduals 
Model assessment based on aggregates of residuals 
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 
Zeroinflation probabilities 
PROC 
PLOTS = 