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From | "Ariel Linden, DrPH" <ariel.linden@gmail.com> |
To | <statalist@hsphsun2.harvard.edu> |
Subject | Re: Re: Re: Re: st: a user-written program for clustering SE on more than one clustering variable? |
Date | Sat, 10 Aug 2013 19:34:10 -0400 |
Nice synopsis, Stas! This mirrors what Rabe-Hesketh & Skrondal (2005)* conclude on page 223 after describing longitudinal, panel and growth-curve models. Ariel Rabe-Hesketh, S. and Skrondal, A. (2005). Multilevel and Longitudinal Modeling using Stata. College Station, TX: Stata Press. ________________________________________ From Stas Kolenikov <skolenik@gmail.com> To "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> Subject Re: Re: Re: st: a user-written program for clustering SE on more than one clustering variable? Date Sat, 10 Aug 2013 11:14:53 -0500 ________________________________________ Defensibility depends on who you talk to. In my experience, economists would be happier with the clustered standard errors, as this method makes fewer assumptions about the data (like the specific structure of the error terms that -xtmixed- has to assume... although it still makes some difficult to assess assumptions of uncorrelatedness of e_it and e_js terms for i!=j, t!=s; violation of this assumption is what produces the negative variance estimates). For health scientists, mixed models are far better understood, give smaller standard errors in small samples (which is what health people apparently have to deal with more often than economists) and the context of the clustered standard errors is mostly that of GEE. Education and psychology people have little clue about clustered standard errors at all, as nearly all of their models are multilevel models (even the name is different!). If I were to see drastically different results from -regress- and -xtmixed-, I would rather want to take -regress- more seriously, as it makes fewer assumptions. Getting the right standard errors is going to be a big pain in the lower back, but if I wouldn't get what I needed from -cmgreg- and the like (once again, -ivreg2- must be able to do this, as far as I can recall, and is in Stata mainstream, meaning better coded, better documented and better understood by the user base), I would look at Art Owen's multiway bootstrap (http://www.citeulike.org/user/ctacmo/article/11402489), although again it makes assumptions similar to those underlying -cmgreg- regarding independence of observations that do not overlap on any dimensions. -- Stas Kolenikov, PhD, PStat (ASA, SSC) -- Senior Survey Statistician, Abt SRBI -- Opinions stated in this email are mine only, and do not reflect the position of my employer -- http://stas.kolenikov.name * * 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/