The PHREG Procedure
- Overview
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Getting Started
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Syntax
PROC PHREG Statement ASSESS Statement BASELINE Statement BAYES Statement BY Statement CLASS Statement CONTRAST Statement EFFECT Statement ESTIMATE Statement FREQ Statement HAZARDRATIO Statement ID Statement LSMEANS Statement LSMESTIMATE Statement MODEL Statement OUTPUT Statement Programming Statements RANDOM Statement STRATA Statement SLICE Statement STORE Statement TEST Statement WEIGHT Statement
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Details
Failure Time Distribution Time and CLASS Variables Usage Partial Likelihood Function for the Cox Model Counting Process Style of Input Left-Truncation of Failure Times The Multiplicative Hazards Model The Frailty Model Hazard Ratios Specifics for Classical Analysis Specifics for Bayesian Analysis Computational Resources Input and Output Data Sets Displayed Output ODS Table Names ODS Graphics
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Examples
Stepwise Regression Best Subset Selection Modeling with Categorical Predictors Firth’s Correction for Monotone Likelihood Conditional Logistic Regression for m:n Matching Model Using Time-Dependent Explanatory Variables Time-Dependent Repeated Measurements of a Covariate Survivor Function Estimates for Specific Covariate Values Analysis of Residuals Analysis of Recurrent Events Data Analysis of Clustered Data Model Assessment Using Cumulative Sums of Martingale Residuals Bayesian Analysis of the Cox Model Bayesian Analysis of Piecewise Exponential Model
- References
| ID Statement |
The ID statement specifies additional variables for identifying observations in the input data. These variables are placed in the OUT= data set created by the OUTPUT statement. In the computation of the COVSANDWICH estimate, you can aggregate over distinct values of these ID variables.
Only variables in the input data set can be included in the ID statement.