The GENMOD Procedure

 
ODS Graphics

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, with 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 39.11, 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 39.11.

To request these graphs, ODS Graphics must be enabled and you must specify the statement and options indicated in Table 39.11.

Table 39.11 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=