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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 in the following table. For more information on ODS, see Chapter 15, "Using the Output Delivery System."

Table 29.3: ODS Tables Produced in PROC GENMOD
ODS Table Name Description Statement Option
ClassLevelsClass variable levelsCLASSdefault
ContrastsTests of contrastsCONTRASTdefault
ContrastCoefContrast coefficientsCONTRASTE
ConvergenceStatusConvergence statusMODELdefault
CorrBParameter estimate correlation matrixMODELCORRB
CovBParameter estimate covariance matrixMODELCOVB
EstimatesEstimates of contrastsESTIMATEdefault
EstimateCoefContrast coefficientsESTIMATEE
GEEEmpPEstGEE parameter estimates with empirical standard errorsREPEATEDdefault
GEELogORInfoGEE log odds ratio model informationREPEATEDLOGOR=
GEEModInfoGEE model informationREPEATEDdefault
GEEModPEstGEE parameter estimates with model-based standard errorsREPEATEDMODELSE
GEENCorrGEE model-based correlation matrixREPEATEDMCORRB
GEENCovGEE model-based covariance matrixREPEATEDMCOVB
GEERCorrGEE empirical correlation matrixREPEATEDECORRB
GEERCovGEE empirical covariance matrixREPEATEDECOVB
GEEWCorrGEE working correlation matrixREPEATEDCORRW
IterContrastsIteration history for contrastsMODEL CONTRASTITPRINT
IterLRCIIteration history for likelihood ratio confidence intervalsMODELLRCI ITPRINT
IterParmsIteration history for parameter estimatesMODELITPRINT
IterParmsGEEIteration history for GEE parameter estimatesMODEL REPEATEDITPRINT
IterType3Iteration history for Type 3 statisticsMODELTYPE3 ITPRINT
LRCILikelihood ratio confidence intervalsMODELLRCI ITPRINT
LSMeanCoefCoefficients for least squares meansLSMEANSE
LSMeanDiffsLeast squares means differencesLSMEANSDIFF
LSMeansLeast squares meansLSMEANSdefault
LagrangeStatisticsLagrange statisticsMODELNOINT | NOSCALE
LastGEEGradLast evaluation of the generalized gradient and HessianMODEL REPEATEDITPRINT
LastGradHessLast evaluation of the gradient and HessianMODELITPRINT
LinDepLinearly dependent rows of contrastsCONTRAST *default
ModelInfoModel informationMODELdefault
ModelfitGoodness-of-fit statisticsMODELdefault
NonEstNonestimable rows of contrastsCONTRAST *default
ObStatsObservation-wise statisticsMODELOBSTATS | CL | PREDICTED | RESIDUALS | XVARS
ParameterEstimatesParameter estimatesMODELdefault
ParmInfoParameter indicesMODEL *default
ResponseProfilesFrequency counts for multinomial modelsMODELDIST=MULTINOMIAL
Type1Type 1 testsMODELTYPE1
Type3Type 3 testsMODELTYPE3

*Depends on data.

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