The GENMOD Procedure

ODS Table Names

PROC GENMOD assigns a name to each table that it creates. You can use these names to reference the table when using the Output Delivery System (ODS) to select tables and create output data sets. These names are listed separately in Table 40.12 for a maximum likelihood analysis, in Table 40.13 for a Bayesian analysis, and in Table 40.14 for an Exact analysis. For more information about ODS, see Chapter 20: Using the Output Delivery System.

Table 40.12: ODS Tables Produced in PROC GENMOD for a Classical Analysis

ODS Table Name

Description

Statement

Option

AssessmentSummary

Model assessment summary

ASSESS

Default

ClassLevels

Classification variable levels

CLASS

Default

Contrasts

Tests of contrasts

CONTRAST

Default

ContrastCoef

Contrast coefficients

CONTRAST

E

ConvergenceStatus

Convergence status

MODEL

Default

CorrB

Parameter estimate correlation matrix

MODEL

CORRB

CovB

Parameter estimate covariance matrix

MODEL

COVB

Estimates

Estimates of contrasts

ESTIMATE

Default

EstimateCoef

Contrast coefficients

ESTIMATE

E

GEEEmpPEst

GEE parameter estimates with empirical standard errors

REPEATED

Default

GEEFitCriteria

GEE QIC fit criteria

REPEATED

Default

GEELogORInfo

GEE log odds ratio model information

REPEATED

LOGOR=

GEEModInfo

GEE model information

REPEATED

Default

GEEModPEst

GEE parameter estimates with model-based standard errors

REPEATED

MODELSE

GEENCorr

GEE model-based correlation matrix

REPEATED

MCORRB

GEENCov

GEE model-based covariance matrix

REPEATED

MCOVB

GEERCorr

GEE empirical correlation matrix

REPEATED

ECORRB

GEERCov

GEE empirical covariance matrix

REPEATED

ECOVB

GEEWCorr

GEE working correlation matrix

REPEATED

CORRW

IterContrasts

Iteration history for contrasts

MODEL CONTRAST

ITPRINT

IterLRCI

Iteration history for likelihood ratio confidence intervals

MODEL

LRCI ITPRINT

IterParms

Iteration history for parameter estimates

MODEL

ITPRINT

IterParmsGEE

Iteration history for GEE parameter estimates

MODEL REPEATED

ITPRINT

IterType3

Iteration history for Type 3 statistics

MODEL

TYPE3 ITPRINT

LRCI

Likelihood ratio confidence intervals

MODEL

LRCI ITPRINT

LSMeanCoef

Coefficients for least squares means

LSMEANS

E

LSMeanDiffs

Least squares means differences

LSMEANS

DIFF

LSMeans

Least squares means

LSMEANS

Default

LagrangeStatistics

Lagrange statistics

MODEL

NOINT | NOSCALE

LastGEEGrad

Last evaluation of the generalized gradient and Hessian

MODEL REPEATED

ITPRINT

LastGradHess

Last evaluation of the gradient and Hessian

MODEL

ITPRINT

LinDep

Linearly dependent rows of contrasts

CONTRAST

Default

ModelInfo

Model information

MODEL

Default

Modelfit

Goodness-of-fit statistics

MODEL

Default without REPEATED

NObs

Number of observations summary

 

Default

NonEst

Nonestimable rows of contrasts

CONTRAST

Default

ObStats

Observation-wise statistics

MODEL

OBSTATS | CL |
PREDICTED |
RESIDUALS | XVARS

ParameterEstimates

Parameter estimates

MODEL

Default without REPEATED |
PRINTMLE with REPEATED

ParmInfo

Parameter indices

MODEL

Default

ResponseProfile

Frequency counts for multinomial and binary models

MODEL

DIST=MULTINOMIAL |
DIST=BINOMIAL

Type1

Type 1 tests

MODEL

TYPE1

Type3

Type 3 tests

MODEL

TYPE3

ZeroParameterEstimates

Parameter estimates for zero-inflated model

ZEROMODEL

Default


Table 40.13: ODS Tables Produced in PROC GENMOD for a Bayesian Analysis

ODS Table Name

Description

Statement

Option

AutoCorr

Autocorrelations of the posterior samples

BAYES

Default

ClassLevels

Classification variable levels

CLASS

Default

CoeffPrior

Prior distribution of the regression coefficients

BAYES

Default

ConvergenceStatus

Convergence status of maximum likelihood estimation

MODEL

Default

Corr

Correlation matrix of the posterior samples

BAYES

SUMMARY=CORR

ESS

Effective sample size

BAYES

Default

FitStatistics

Fit statistics

BAYES

Default

Gelman

Gelman and Rubin convergence diagnostics

BAYES

DIAG=GELMAN

Geweke

Geweke convergence diagnostics

BAYES

Default

Heidelberger

Heidelberger and Welch convergence diagnostics

BAYES

DIAG=HEIDELBERGER

InitialValues

Initial values of the Markov chains

BAYES

Default

IterParms

Iteration history for parameter estimates

MODEL

ITPRINT

LastGradHess

Last evaluation of the gradient and Hessian for maximum likelihood estimation

MODEL

ITPRINT

MCError

Monte Carlo standard errors

BAYES

DIAG=MCSE

ModelInfo

Model information

PROC

Default

NObs

Number of observations

 

Default

ParameterEstimates

Maximum likelihood estimates of model parameters

MODEL

Default

ParmInfo

Parameter indices

MODEL

Default

ParmPrior

Prior distribution for scale and shape

BAYES

Default

PostIntervals

HPD and equal-tail intervals of the posterior samples

BAYES

Default

PosteriorSample

Posterior samples (for ODS output data set only)

BAYES

 

PostSummaries

Summary statistics of the posterior samples

BAYES

Default

Raftery

Raftery and Lewis convergence diagnostics

BAYES

DIAG=RAFTERY


Table 40.14: ODS Tables Produced in PROC GENMOD for an Exact Analysis

ODS Table Name

Description

Statement

Option

ExactOddsRatio

Exact odds ratios

EXACT

ESTIMATE=ODDS,
ESTIMATE=BOTH

ExactParmEst

Parameter estimates

EXACT

ESTIMATE, ESTIMATE=PARM, ESTIMATE=BOTH

ExactTests

Conditional exact tests

EXACT

Default

NStrataIgnored

Number of uninformative strata

STRATA

Default

StrataSummary

Number of strata with specific response frequencies

STRATA

Default

StrataInfo

Event and nonevent frequencies for each stratum

STRATA

INFO

SuffStats

Sufficient statistics

EXACT

OUTDIST=