| From | "Nick Winter" <nwinter@policystudies.com> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | st: Repeated measures testing |
| Date | Mon, 26 Aug 2002 15:22:25 -0400 |
Greetings, In some survey data, I have three variables that measure whether a given school improvement strategy is used with each of three types of schools, A, B, and C. (Variables d1a, d1b, d1c -- d1a codes as a 0/1 whether or not strategy one is used with school type A; d1b records the same thing for school type b, and so on). I'm interested in testing whether a strategy is used differentially for different types of schools. If there were two school types, this would be easy -- simply -ttest- that the two variables are equal: . ttest d1a = d1b But with three, it gets more complex. One approach, since this is survey data, is to first use -svymean- to get the means of all three, then test jointly that a=b and a=c: . svymean d1a d1b d1c, complete . svytest d1a=d1b, notest . svytest d1a=d1c, accum Another approach would be to set it up as a repeated measures ANOVA -- reshaping to long format, and treating the three types as a repeated measure. But with thousands of cases, this seems cumbersome at best. Thoughts? Thanks, Nick Winter ----------------------------------------------------------- Nicholas Winter, Ph.D. P 202.939.5343 Policy Studies Associates F 202.939.5732 1718 Connecticut Avenue, NW nwinter@policystudies.com Washington, DC 20009-1148 www.policystudies.com -----------------------------------------------------------
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