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From |
"Jessica Gottlieb" <jgott@stanford.edu> |

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

Subject |
st: permute with multi-level models |

Date |
Tue, 11 Oct 2011 18:27:43 -0700 |

Hi, I am trying to run a Monte Carlo simulation on a mixed model regression to infer standard errors and p values. I am using the permute command after running a multi-level model with xtmixed (see below). The treatment variable t has 3 values {0,1,2} and I am interested in estimating the coefficients using i.t. The data is multi-level in which individuals are nested within villages which are nested within communes (reflected in the random effects). program pxtmixed, rclass xtmixed trust i.t || commune: || village: matrix x=e(b) return scalar t1 = x[1, 2] end permute t r(t1), reps(1000): pxtmixed I have 2 major questions: 1. I want to permute t across communes such that the value of t is uniform for all individuals within a given commune. Does anyone have thoughts on how to do this? 2. I am interested in estimating p values for 2 coefficients, but when I try to return a matrix rather than a scalar (see below), the command doesn't go through. I get an error that says "weights not allowed". program pxtmixed, rclass xtmixed trustcouncil i.t || commune: || village: matrix x=e(b)' return matrix coeff = x[2..3, 1] end permute t r(coeff), reps(1000): pxtmixed Thanks for any advice on these questions, Jessica * * 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/

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