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The LOGISTIC Procedure
Overview
Getting Started
Syntax
PROC LOGISTIC Statement
BY Statement
CLASS Statement
CONTRAST Statement
EFFECT Statement
EFFECTPLOT Statement
ESTIMATE Statement
EXACT Statement
EXACTOPTIONS Statement
FREQ Statement
LSMEANS Statement
LSMESTIMATE Statement
MODEL Statement
ODDSRATIO Statement
OUTPUT Statement
ROC Statement
ROCCONTRAST Statement
SCORE Statement
SLICE Statement
STORE Statement
STRATA Statement
TEST Statement
UNITS Statement
WEIGHT Statement
Details
Missing Values
Response Level Ordering
Link Functions and the Corresponding Distributions
Determining Observations for Likelihood Contributions
Iterative Algorithms for Model Fitting
Convergence Criteria
Existence of Maximum Likelihood Estimates
EffectSelection Methods
Model Fitting Information
Generalized Coefficient of Determination
Score Statistics and Tests
Confidence Intervals for Parameters
Odds Ratio Estimation
Rank Correlation of Observed Responses and Predicted Probabilities
Linear Predictor, Predicted Probability, and Confidence Limits
Classification Table
Overdispersion
The HosmerLemeshow GoodnessofFit Test
Receiver Operating Characteristic Curves
Testing Linear Hypotheses about the Regression Coefficients
Regression Diagnostics
Scoring Data Sets
Conditional Logistic Regression
Exact Conditional Logistic Regression
Input and Output Data Sets
Computational Resources
Displayed Output
ODS Table Names
ODS Graphics
Examples
Stepwise Logistic Regression and Predicted Values
Logistic Modeling with Categorical Predictors
Ordinal Logistic Regression
Nominal Response Data: Generalized Logits Model
Stratified Sampling
Logistic Regression Diagnostics
ROC Curve, Customized Odds Ratios, GoodnessofFit Statistics, RSquare, and Confidence Limits
Comparing Receiver Operating Characteristic Curves
GoodnessofFit Tests and Subpopulations
Overdispersion
Conditional Logistic Regression for Matched Pairs Data
Firth’s Penalized Likelihood Compared with Other Approaches
Complementary LogLog Model for Infection Rates
Complementary LogLog Model for IntervalCensored Survival Times
Scoring Data Sets
Using the LSMEANS Statement
References
Examples: LOGISTIC Procedure
Stepwise Logistic Regression and Predicted Values
Logistic Modeling with Categorical Predictors
Ordinal Logistic Regression
Nominal Response Data: Generalized Logits Model
Stratified Sampling
Logistic Regression Diagnostics
ROC Curve, Customized Odds Ratios, GoodnessofFit Statistics, RSquare, and Confidence Limits
Comparing Receiver Operating Characteristic Curves
GoodnessofFit Tests and Subpopulations
Overdispersion
Conditional Logistic Regression for Matched Pairs Data
Firth’s Penalized Likelihood Compared with Other Approaches
Complementary LogLog Model for Infection Rates
Complementary LogLog Model for IntervalCensored Survival Times
Scoring Data Sets
Using the LSMEANS Statement
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