The LOGISTIC Procedure

ODS Table Names

PROC LOGISTIC assigns a name to each table it creates. You can refer to the tables by these names when you use the Output Delivery System (ODS) to select tables and create output data sets. These names are listed in Table 17. For more information about ODS, see Chapter 23, Using the Output Delivery System.

The EFFECT, ESTIMATE, LSMEANS, LSMESTIMATE, MARGINS, and SLICE statements also create tables, which are not listed in Table 17. For information about these tables, see the corresponding sections of Chapter 20, Shared Concepts and Topics.

Table 17: ODS Tables Produced by PROC LOGISTIC

ODS Table Name Description Statements Options
Areas Area under the curves PROC LOGISTIC ROCOPTIONS(AREA)
(with ROC and PR curves)
Association Association of predicted probabilities and observed responses MODEL
(without STRATA)
Default
BestSubsets Best subset selection MODEL SELECTION=SCORE
ClassFreq Frequency breakdown of CLASS variables PROC LOGISTIC SIMPLE (with CLASS
variables)
Classification Classification table MODEL CTABLE
ClassLevelInfo CLASS variable levels and design variables MODEL Default (with CLASS
variables)
ClassWgt Weight breakdown of CLASS variables PROC LOGISTIC,
WEIGHT
SIMPLE (with CLASS
variables)
CLOddsPL Odds ratio estimates and profile-likelihood confidence intervals MODEL CLODDS=PL
CLOddsWald Odds ratio estimates and Wald confidence intervals MODEL CLODDS=WALD
CLParmPL Parameter estimates and profile-likelihood confidence intervals MODEL CLPARM=PL
CLParmWald Parameter estimates and Wald confidence intervals MODEL CLPARM=WALD
ContrastCoeff L matrix from CONTRAST CONTRAST E
ContrastEstimate Estimates from CONTRAST CONTRAST ESTIMATE=
ContrastTest Wald test for CONTRAST CONTRAST Default
ConvergenceStatus Convergence status MODEL Default
CorrB Estimated correlation matrix of parameter estimators MODEL CORRB
CovB Estimated covariance matrix of parameter estimators MODEL COVB
CumulativeModelTest Test of the cumulative model assumption MODEL Default with cumulative
response
EffectInModel Test effects in model MODEL SELECTION=S | B
EffectNotInModel Test for effects not in model MODEL SELECTION=S | F
ExactOddsRatio Exact odds ratios EXACT ESTIMATE=ODDS,
ESTIMATE=BOTH
ExactParmEst Parameter estimates EXACT ESTIMATE, ESTIMATE=PARM, ESTIMATE=BOTH
ExactTests Conditional exact tests EXACT Default
FastElimination Fast backward elimination MODEL SELECTION=B, FAST
FitStatistics Model fit statistics MODEL Default
GlobalScore Global score test MODEL NOFIT
GlobalTests Test for global null hypothesis MODEL Default
GoodnessOfFit Pearson and deviance goodness-of-fit tests MODEL SCALE, GOF
IndexPlots Batch capture of the index plots MODEL IPLOTS
Influence Regression diagnostics MODEL INFLUENCE
IterHistory Iteration history MODEL ITPRINT
LackFitChiSq Hosmer-Lemeshow chi-square test results MODEL LACKFIT, GOF
LackFitPartition Partition for the Hosmer- Lemeshow test MODEL LACKFIT, GOF
LastGradient Last evaluation of gradient MODEL ITPRINT
Linear Linear combination PROC LOGISTIC Default
LogLikeChange Final change in the log likelihood MODEL ITPRINT
ModelANOVA Joint or Type 3 tests of effects MODEL Default (with
CLASS variables)
ModelBuildingSummary Summary of model building MODEL SELECTION=B | F | S
ModelInfo Model information PROC LOGISTIC Default
NObs Number of observations PROC LOGISTIC Default
OddsEst Adjusted odds ratios UNITS Default
OddsRatios Odds ratio estimates MODEL Default
OddsRatiosPL Odds ratio estimates and PL confidence intervals ODDSRATIOS CL=PL
OddsRatiosWald Odds ratio estimates and Wald confidence intervals ODDSRATIOS CL=WALD
ParameterEstimates Maximum likelihood estimates of model parameters MODEL Default
ResidualChiSq Residual chi-square MODEL SELECTION=F | B
ResponseProfile Response profile PROC LOGISTIC Default
ROCAssociation Association table for ROC models ROC
MODEL
Default
ROCCI
ROCContrastCoeff L matrix from ROCCONTRAST ROCCONTRAST E
ROCContrastCov Covariance of ROCCONTRAST rows ROCCONTRAST COV
ROCContrastEstimate Estimates from ROCCONTRAST ROCCONTRAST ESTIMATE=
ROCContrastTest Wald test from ROCCONTRAST ROCCONTRAST Default
ROCCov Covariance between ROC curves ROCCONTRAST COV
RSquare R-square MODEL RSQUARE
ScoreFitStat Fit statistics for scored data SCORE FITSTAT
SimpleStatistics Summary statistics for explanatory variables PROC LOGISTIC SIMPLE
StrataInfo Event and nonevent frequencies for each stratum STRATA INFO
StrataSummary Number of strata with specific response frequencies STRATA Default
SuffStats Sufficient statistics EXACT OUTDIST=
TestPrint1 L[Cov(b)]L’ and Lb-c TEST PRINT
TestPrint2 Ginv(L[Cov(b)]L’) and
Ginv(L[Cov(b)]L’)(Lb-c)
TEST PRINT
TestStmts Linear hypotheses testing results TEST Default


Last updated: December 09, 2022