[R] svycoxph and test statistics

[Terry Therneau]

On 03/24/2012 06:00 AM, r-help-request at r-project.org wrote:
> I have been using the function 'svycoxph' in the Dr. Lumley's survey package (version 3.26) to compute coefficient estimates for Cox regression.
>
> I have noticed the p-values output are based on normal distribution (like in coxph); however in svyglm (and in other software, such as Stata or SAS) the p-values are computed via the t distribution with degrees of freedom equal to the number of PSUs minus number of strata.
>
> I am wondering why there is a difference here?
I'm not aware of any theory papers that back up the use of a 
t-distribution.  This is a Cox model, and "do what my Gaussian package 
does" is not usually the best approach.  I'm far from an expert in 
survey work though, so I'll yeild to Thomas L for a definitive answer.
   In the case of mixed effects models I see the exact same leaning 
towards (approximate) REML vs ML; this is an area that I do know deeply 
and and the "REML better than ML" arguments from linear mixed effects 
models to NOT transfer over.

Terry Therneau