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From |
Jeph Herrin <junk@spandrel.net> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: ttest or xtmelogit? |

Date |
Mon, 10 Mar 2008 18:39:39 -0400 |

You may want to look at a program I wrote called -clchi2-, which is part of the package -cltest- on SSC. This performs a chi2 test of independence, adjusted for clustering. It implements an adjustment suggested by Donner & Klar (don't recall the original paper, but it's in Cluster Randomization Trials in Health Services Research, 2000). It needs only 3 clusters per comparison group to estimate the intra-cluster correlation (though it doesn't account for the uncertainty in basing the ICC on such a small number of clusters). hth, Jeph David Airey wrote:

.

I have a typical pilot data set. Small. I have 12 mice, 6 from one group, 6 from another. For each mouse I have about 50 yes/no scores. 50 was enough to get precision on a given mouse. I'm interested in the group difference. In the past I used xtgee with mouse as the i(mouse) option, i.e., mouse as the cluster, with family(binomial) and link(logit). But previously, I did this with double the number of mice, so I felt I had enough clusters. Here, I am feeling uncomfortable about the number of clusters (12). The same goes for xtmelogit, new in Stata 10. Given the number of mice, is it better to simply transform the summary statistics for animals (mean of the yes/no vector by animal), like with an arcsine or logit, and use a ttest?

-Dave

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**Follow-Ups**:**Re: st: ttest or xtmelogit?***From:*David Airey <david.airey@vanderbilt.edu>

**References**:**st: ttest or xtmelogit?***From:*David Airey <david.airey@Vanderbilt.Edu>

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