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From | Jordan Silberman <silberman.stata@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | st: Mixed model degrees of freedom and Stata presentation |
Date | Sat, 17 Nov 2012 16:05:40 -0500 |
Hi Stata folks, My department is abandoning SPSS, and instead will begin teaching courses with a different package--probably R, SAS, or Stata. I've been a Stata fan for years, and I'm going to give a presentation to the department on pros/cons of Stata. It seems to me that Stata beats or at least ties other packages for most criteria, but there is one area in which Stata seems to be behind--df estimation for mixed models. Unfortunately, this could be a deal-breaker for many researchers in our department. I understand that this is not an issue for large samples, but it is an issue when samples are small. And even when samples are large enough that differences between z and t significance levels are trivial, the fact is, reviewers in some fields may still expect df values to be reported for multilevel models (whether or not this expectation is justified). So, a few questions: 1. Are there plans to provide more extensive options for df estimation (eg, Kenward-Roger, Satterthwaite, etc.) with xtmixed/xtmelogit in the future? This feature would be extremely helpful, even if just one estimation method is provided. 2. I have read that Stata statisticians believe there's no defensible way to estimate df for mixed models. Can anyone explain why this is so, preferably in language a non-statistician can understand? 3. The solution to this problem offered in Stata is to assume infinite degrees of freedom. It seems to me, from a statistically naive perspective, that it is literally mathematically impossible to use a less defensible solution. It's not possible to provide a df estimate that is further from the true df value than infinite. But I suspect that there's more to it than this. Can anyone explain why assuming that df = infinite is more defensible than other df estimation methods, even though other methods are mathematically guaranteed to provide more accurate df estimates? 4. What can I say to researchers who publish in journals in which reviewers are used to seeing dfs reported with multilevel models about the possibility of using Stata to estimate their multilevel models? Any thoughts would be greatly appreciated. Thanks, Jordan * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/