MARY A. WEISS <mweiss <at> temple.edu> writes: > > Hi, > > I am currently using STATA in my analysis. STATA has a cluster option but > does not have any tests for whether cluster analysis is necessary or not for > a dataset. So I am trying to figure out whether R could be used to test > whether I need to be doing cluster analysis or not. If R does tests to > determine whether cluster analysis is valid for my data, I will learn R and > use it on my data. > > My data are panel data consisting of 49 states and 25 years. Currently, I > am estimating models with fixed state and time effects. > > Thanks for any help you can give me. > > Cheers, > > Mary
You might want to forward this question to the r-sig-mixed-models list. I think you are fairly far off base in comparing 'prabclus' (spatial clustering) to what Stata means by "clustered standard errors" (e.g. <http://www.stata.com/support/faqs/stat/cluster.html>). Cluster _analysis_ has to do with finding clusters in data; prabclus uses spatial information to do cluster analysis; robust cluster variances or standard errors have to do with adjusting variance/SE to account for predetermined grouping variables ("clusters" in the data, e.g. states). I don't know offhand whether there are packages in R that implement the "robust cluster variance" estimator; packages like geeglm, geepack, and especially the "sandwich" package are definitely worth looking at (they implement the equivalent of robust, but not robust cluster [as far as I can tell], variance estimators]), as well as the Econometrics Task View and the book "R for Stata Users" by Muenchen and Hilbe. A final philosophical note: I don't think you should be testing _based on your data_ whether robust or robust cluster variance estimators are more appropriate; there's a fairly dangerous data snooping issue here. Rather, you should try to decide _a priori_ based on your data what's most appropriate. Ben Bolker > > On Mon, May 2, 2011 at 1:02 PM, Tal Galili <tal.galili <at> gmail.com> wrote: > > > Hi Mary, > > Are you using R for your other analysis? > > If so, What commands are you using for your analysis? > > > > p.s: please keep the rest of the R-help mailing list in the loop. > > > > Cheers, > > Tal > > > > > > [snip] > > > > > > > > > [snip] MARY A. WEISS <mweiss <at> temple.edu> wrote: > > > >> Hi Tal, > >> > >> Thanks for your answer. I am running models with two-way fixed effects > >> and two-way fixed effects with a cluster option. The results are very > >> different. I wanted to know if it is appropriate to cluster my data or > >> not. In looking through the R manual, > >> I thought that prabclus might help me > >> answer the question. Does prabclus include any tests that will tell me if > >> cluster analysis is appropriate to use with my data? That is, is cluster > >> analysis valid for my data? > >> > >> Thanks in advance for any help you can give me. I really appreciate it. > >> > >> Mary > >> [snip] > >> > >>> Hi Mary, > >>> I'm not sure I understood your question. > >>> > >>> Are you using this package: > >>> http://cran.r-project.org/web/packages/prabclus/index.html > >>> <http://cran.r-project.org/web/packages/prabclus/index.html>And asking > >>> how to decide if to use it or not? > >>> > >>> ----------------Contact > >>> Details:------------------------------------------------------- > >>> Contact me: Tal.Galili <at> gmail.com | 972-52-7275845 > >>> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | > >>> www.r-statistics.com (English) > >>> > >>> > >>> > >>> > >>> > >>> > >>> > >>> On Sun, May 1, 2011 at 7:54 PM, mary weiss <mweiss <at> temple.edu> wrote: > >>> > >>>> Does R have the capability to perform tests for the need of clustering > >>>> analysis (e.g., in prabclus)? I am using panel data with two-way fixed > >>>> effects but am unsure about whether I should be using a cluster option > >>>> as > >>>> well to estimate my model.-- > >>>> [snip] ______________________________________________ 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.
