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From |
"Joseph Coveney" <jcoveney@bigplanet.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Estimating the (possibly negative) intracluster correlation |

Date |
Tue, 7 Sep 2010 02:17:26 +0900 |

Scott Baldwin wrote: One option is to use the residuals option with an exchangeable correlation structure in xtmixed. This allows you to look at the correlation among observations within a cluster rather than the variance among the cluster means (as would be the case if you fit a random intercept model). [remainder omitted] -------------------------------------------------------------------------------- That is neat. I'll really have to start getting familiar with what -xtmixed- and its new -residuals()- option can do. The ovary dataset doesn't have a negative ICC, but the artificial dataset below does have a negative ICC to illustrate Scott's -xtmixed- approach. I'd known that you can do it with -xtgee- (so long as it's a linear model), and with the old method-of-moments technique with -anova- (for a balanced dataset). For some reason, I'd always thought that an ML (REML) method couldn't deal with negative ICCs, and that you had to resort to ANOVA and method-of-moments, because they admit negative variance components estimates, or to GEE. Joseph Coveney version 11.1 clear * set more off set seed `=date("2010-09-07", "YMD")' matrix input C = (1 -0.7 \ -0.7 1) drawnorm mu0 mu1, corr(C) n(200) clear generate int pid = _n quietly reshape long mu, i(pid) j(tim) xtmixed mu i.tim || pid:, nocons residuals(exchangeable) /// nolrtest nolog xtgee mu i.tim, i(pid) estat wcor anova mu pid tim scalar define sigma2_e = e(rss) / e(df_r) scalar define sigma2_u = /// (e(ss_1) / e(df_1) - sigma2_e) / (e(df_2) + 1) scalar define ICC = sigma2_u / (sigma2_u + sigma2_e) display in smcl as text ICC exit * * 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/

**Follow-Ups**:**Re: st: Estimating the (possibly negative) intracluster correlation***From:*Bert Jung <bjung59@gmail.com>

**References**:**st: Estimating the (possibly negative) intracluster correlation***From:*Bert Jung <bjung59@gmail.com>

**Re: st: Estimating the (possibly negative) intracluster correlation***From:*Scott Baldwin <baldwinlist@gmail.com>

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