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From |
Richard Goldstein <richgold@ix.netcom.com> |

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

Subject |
st: sampling query |

Date |
Thu, 27 Jan 2011 11:37:16 -0500 |

all, I have received a report in which the report writer was stuck with the following design (already implemented before his involvement): a number of "cohorts" were set up (22 of them in fact) and the definitions of these cohorts were not mutually exclusive (i.e., there was some overlap in membership so that a given observation could appear in more than 1 cohort); to calculate the probability weights, the report writer first calculated the probability of inclusion for each cohort (simply as n/N where n is sample size from cohort and N is population size of cohort). For observations in more than one cohort, who were actually selected, he then multiplied the inclusion probabilities of each cohort that observations was in. Since each inclusion probability is less than 1, the combined inclusion probability is smaller than the individual inclusion probabilities for the individual cohort. And then, of course, the weights are greater for these people (since the weight is just the inverse of the inclusion probability). However, since these observations are in more than one cohort, shouldn't the combined probability be greater for them (rather than smaller)? How should the combined inclusion probability be calculated? Or am I just wrong and the writer of the report is correct? Any references on dealing with overlapping "cohorts" would also be greatly appreciated. Rich * * 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: sampling query***From:*Stas Kolenikov <skolenik@gmail.com>

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