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From |
"Stas Kolenikov" <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: matching procedure |

Date |
Wed, 7 May 2008 08:52:34 -0500 |

Propensity score matching implies there are differential probabilities in being in each of the sub-samples, and you are trying to match based on those probabilities (which is a sufficient statistic under some relatively restrictive assumptions). If you have a perfectly randomized allocation (which you did not mention, but that's probably the most important question for your design), then all propensity scores should be 1/2, and you won't get any informative matches on those. There are alternative matching procedures based on the distances in demographic space -- see -nnmatch- by Guido Imbens and Co. In fact, if you only want to do matching, you should try some of the -cluster- methods, although you would need to tweak them into recognizing two groups. Having those perfectly isolated samples for project comparison is not making much sense, indeed. If you wanted to save on respondent burden, you should've used some sort of fractional design scheme where each respondent is asked only half questions, but that half is carefully selected and rotated around in a balanced way, so that each pair of questions is answered by the same number of respondents. On 5/7/08, Richter, Ansgar <Ansgar.Richter@ebs.edu> wrote: > I have a question regarding statistical matching of two samples. My problem > is as follows: > > Research design: Two samples (A, B) with 180 individual respondents each. > Same 16 questions were asked for 4 different project settings (equals 64 > variables). In each project setting, Sample A respondents answered 8 of the > questions, the other 8 questions were answered by B respondents. > > The problem is that each observation has always 32 missing values. Example > of data structure for questions 6-11 in project setting 1 for respondents > 351-355 > > 351. | . . . 2 6 4 | > 352. | 3 6 7 . . . | > 353. | . . . 5 5 4 | > 354. | . . . 2 4 7 | > 355. | 6 6 6 . . . | > > Objective: Match A and B respondents to have all 16 questions for each > project setting answered per observation resulting in a sample size of 180 > paired respondents (necessary for ANOVA). Respondents are supposed to be > matched (paired) based on demographic variables which were answered by each > respondent. > > I tried psmatch2 in Stata but it seems that I can't use this function for > this design. Do you have any suggestions as to how I could achieve the > matching that I envisage? -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: Please do not reply to my Gmail address as I don't check it regularly. * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: matching procedure***From:*"Richter, Ansgar" <Ansgar.Richter@ebs.edu>

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