The SURVEYPHREG Procedure
- Overview
- Getting Started
-
Syntax
PROC SURVEYPHREG Statement BY Statement CLASS Statement CLUSTER Statement DOMAIN Statement ESTIMATE Statement FREQ Statement LSMEANS Statement LSMESTIMATE Statement MODEL Statement NLOPTIONS Statement OUTPUT Statement Programming Statements REPWEIGHTS Statement SLICE Statement STORE Statement STRATA Statement TEST Statement WEIGHT Statement -
Details
Notation and Estimation Failure Time Distribution Time and CLASS Variables Usage Partial Likelihood Function for the Cox Model Specifying the Sample Design Missing Values Variance Estimation Domain Analysis Hypothesis Tests, Confidence Intervals, and Residuals Output Data Sets Displayed Output ODS Table Names ODS Graphics
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Examples
- References
Testing the Global Null Hypothesis
The following statistics can be used to test the global null hypothesis 
=
. Let 
be the number of clusters (or observations) minus the number of strata (or one) and 
be the number of estimable parameters in the analysis model.
The likelihood ratio test is expressed as
 |
where L(
) denotes the partial pseudo-likelihood described in Partial Likelihood Function for the Cox Model. The p-value is computed by using a chi-square distribution with degrees of freedom. The usual assumptions required for a likelihood ratio test do not hold for the pseudo-likelihood that is used by PROC SURVEYPHREG, leading to other methods for testing the global null hypothesis, such as the Wald test discussed below.
Wald’s test is expressed as
 |
The p-value is computed by using an F distribution with 
degrees of freedom. For the Taylor series linearization method, the DF=PARMADJ option in the MODEL statement computes the p-value by using an F distribution with 
degrees of freedom.
If you specify the DF=NONE option in the MODEL statement, then the procedure computes
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and the p-value is computed by using a chi-square distribution with degrees of freedom.