The LOGISTIC Procedure

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

Simple
(with CLASS vars)

ClassLevelInfo

CLASS variable levels and design variables

MODEL

Default
(with CLASS vars)

Classification

Classification table

MODEL

CTABLE

ClassWgt

Weight breakdown of CLASS variables

PROC, WEIGHT

Simple
(with CLASS vars)

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

(Ordinal response)

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

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

LackFitPartition

Partition for the Hosmer- Lemeshow test

MODEL

LACKFIT

LastGradient

Last evaluation of gradient

MODEL

ITPRINT

Linear

Linear combination

PROC

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

Default

NObs

Number of observations

PROC

Default

OddsEst

Adjusted odds ratios

UNITS

Default

OddsRatios

Odds ratio estimates

MODEL

Default

OddsRatiosWald

Odds ratio estimates and Wald confidence intervals

ODDSRATIOS

CL=WALD

OddsRatiosPL

Odds ratio estimates and PL confidence intervals

ODDSRATIOS

CL=PL

ParameterEstimates

Maximum likelihood estimates of model parameters

MODEL

Default

RSquare

R-square

MODEL

RSQUARE

ResidualChiSq

Residual chi-square

MODEL

SELECTION=F|B

ResponseProfile

Response profile

PROC

Default

ROCAssociation

Association table for ROC models

ROC

Default

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

ScoreFitStat

Fit statistics for Scored data

SCORE

FITSTAT

SimpleStatistics

Summary statistics for explanatory variables

PROC

SIMPLE

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=

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