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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Instrumental Variables approach using -xt- for three-level growth model |

Date |
Mon, 6 May 2013 10:18:40 -0400 |

David Torres <writeon4truth2@msn.com> You don't specify, but I assume you have 5 plausible values drawn from a posterior distribution on achievement from some standardized test as your outcome variable, and school type attended as your explanatory variable of interest--none of the variables you cite satisfy an exclusion restriction, as all would be expected to have direct impacts on achievement. If you do in fact have 5 plausible values as your outcome measure, you should not be using -xtmixed- IMHO but perhaps -mi- since these are 5 imputations for one observation, not 5 observations. If you have 5 plausible values at two points in time, you now have 25 imputations, and so on. You should get similar results if you just average across the 5 imputations, but no identical of course. The more important challenge is finding good instruments for school type attended. Do you know where people live relative to the boundary of the "zoned school area" so you can compute that distance precisely? Do boundaries change over time? On Sun, May 5, 2013 at 4:57 PM, David Torres <writeon4truth2@msn.com> wrote: > Hey, all, > > I would like to utilize the instrumental variables approach with hierarchical data that has repeated measures (five) of students nested within schools. I'd prefer to do this in HLM7, but I'm not sure if the program allows for this more complex model setup. Anyway, I know Stata has the -xtivreg- command. Is there something similar for mixed effects models, i.e., -xtivmixed- perhaps? If not, how can I accomplish my aim using what's available in Stata. (I do have the Rabe-Hesketh & Skrondal texts.) > > I am instrumenting for the likelihood of parents exercising choice to send their children to a school outside the zoned school area. Obviously, self-selection is an issue here, but proxies that might explain the likelihood of choice are, and this list is by no means exhaustive, number of older children in the household, maternal education, or percent of persons over 18 with a bachelor's degree...or something like that. HELP. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: Instrumental Variables approach using -xt- for three-level growth model***From:*David Torres <writeon4truth2@msn.com>

**References**:**st: Instrumental Variables approach using -xt- for three-level growth model***From:*David Torres <writeon4truth2@msn.com>

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