Thank you, Dr. Therneau... I got a similar answer from Dr. Lumley: On Mar 24, 2012, at 4:05 PM, Thomas Lumley wrote:
> As far as I know there isn't any theoretical justification for the > t-distribution but it empirically works better. > > You can get tests with a t or F reference distribution easily with > regTermTest. You can also get likelihood ratio tests that way, which > appear to have slightly better small-sample performance than the > standard Wald tests. > > - thomas On Mar 25, 2012, at 5:17 PM, Terry Therneau wrote: > On 03/24/2012 06:00 AM, r-help-requ...@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 > > > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
