


The following statistics can be used to test the global null hypothesis
. Under mild assumptions, each statistic has an asymptotic chi-square distribution with
degrees of freedom given the null hypothesis. The value
is the dimension of
. For clustered data, the likelihood ratio test, the score test, and the Wald test assume independence of observations within
a cluster, while the robust Wald test and the robust score test do not need such an assumption.
![\[ \chi ^2_{\mr{RS}} = \left[\sum _ i \bL ^0_ i \right]’ \left[ \sum _ i \bL ^0_ i{\bL ^0_ i}’ \right] ^{-1} \left[\sum _ i \bL ^0_ i \right] \]](images/statug_phreg0445.png)
where
is the score residual of the ith subject at
; that is,
, where the score process
is defined in the section Residuals.
![\[ \chi ^{2}_{\mr{RW}}=\hat{\bbeta }’ [\hat{\bV }_ s(\hat{\bbeta })]^{-1} \hat{\bbeta } \]](images/statug_phreg0450.png)
where
is the sandwich variance estimate. For more information, see the section Robust Sandwich Variance Estimate.