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From | "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk> |
To | <statalist@hsphsun2.harvard.edu> |
Subject | RE: st: Simultaneously accounting for clustering at two different levels with vce(cluster) option |
Date | Thu, 11 Mar 2010 12:48:31 -0000 |
Misha, lilyyor1, > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of > Misha Spisok > Sent: Thursday, March 11, 2010 5:39 AM > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: Simultaneously accounting for clustering at > two different levels with vce(cluster) option > > See, also, Cameron, Gelbach, and Miller, Robust Inference with > Multi-way Clustering, for which, I believe, the authors have developed > a Stata package. I don't think this will work in this applications, for 2 reasons. First, the Cameron-Gelbach-Miller-Thompson approach is for non-nested clusters (I think that's why they call it "multi-way" rather than "multi-level"). In lilyyor1's application, classrooms are nested in schools. Second, the cluster-robust approach in general requires the number of clusters to go off to infinity. 8 schools is not very far on the way to infinity! HTH, Mark > > On Tue, Mar 9, 2010 at 11:40 AM, Lily Yor <lilyyor1@gmail.com> wrote: > > Hi, I have data that is clustered at two different levels > -- i.e., I have > > data at classroom level and at school level. I need to > account for these > > two sets of intraclass clustering, but the clusters at each > level are too > > few to run a formal multi-level model (for example, there > are only 8 schools > > in my data). Thus, I would like to run a logistic > regression model (my > > dependent variable is binary -- whether a student has > passed a certain test > > or not) and adjust the standard errors by using > vce(cluster) option, but > > there doesn't seem to be a way to simultaneously, in a > single model, account > > for clustering at both levels (i.e., classroom level and > school level). > > > > The way I have approached this problem thusfar is to run > the logistic > > regression model with vce(cluster) option applied to > account for classroom > > clustering, and then include school dummies in the same > model, but this does > > not seem to be a satisfactory solution: > > > > logit [dep var] [ind_var1] [ind_var2] [ind_var3] [school2] > [school3] > > [school4] [school5] [school6] [school7] [school8], > vce(cluster classroom_id) > > > > If you have any tips and suggestions on how I could use the > vce(cluster) > > option to account for both classroom and school clustering, > I would very > > much appreciate your help. > > > > Thank you so much. > > > > * > > * For searches and help try: > > * http://www.stata.com/help.cgi?search > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Heriot-Watt University is a Scottish charity registered under charity number SC000278. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/