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From |
Jacob Wegelin <jacob.wegelin@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: non-nested random effects |

Date |
Mon, 6 Apr 2009 18:54:15 -0400 |

I am looking for a way to fit a linear mixed-effects model with non-nested, as distinguished from crossed, random effects. I know how to do this in a competing software package (R, www.r-project.org, the lme4 library), and would like to do it in Stata instead. My attempt with xtmixed does not reproduce what I am able to do in R. Details: Suppose that a group of individuals ran a yearly race over 22 years. Some ran it only once; some ran it many times. The outcome is the time they took to finish. Because almost 3000 people participated over the years, the data contain over 5000 observations. I want to fit a linear mixed-effects model with two, non-nested, random intercepts: NAME (the runner's ID) and Year. Fixed effects include the runner's age and sex and the ambient temperature on the day of the run. Note that Year, as a random effect, is categorical and is distinct from runner's age. I believe that the Year random effect is necessary because years differ from each other in ways not captured by the data. I assume that the Year and NAME random effects are independent from each other, and that errors are independent conditioned on the model. The following code does not yield the desired result: -xtmixed FinishTime Sex01F PL2Age2 Sex01FxPL2Age2 PL2Age3 nFin1974toPrev MinCC PzCDrp MinCCxPzCDrp || NAME: || Year: - because it "thinks" that Year takes on as many levels as there are rows in the data, rather than 22 levels. This is shown by the following fragment of output from the above command: Mixed-effects REML regression Number of obs = 5276 ----------------------------------------------------------- | No. of Observations per Group Group Variable | Groups Minimum Average Maximum ----------------+------------------------------------------ NAME | 2933 1 1.8 21 Year | 5276 1 1.0 1 ----------------------------------------------------------- In R (www.r-project.org, the lme4 library) I am able to fit the model I want. The output includes 2933 BLUPs (best linear unbiased predictors) for NAME random effects and only 22 BLUPs for Year random effects. In particular, the software does not think that Year takes on 5276 levels. Is there a way to fit such a model in Stata? Rabe-Hesketh (2005), Multilevel and Longitudinal Modeling Using Stata, has a chapter on "crossed random effects." But this appears to lead to the kind of model fit above by xtmixed. Thanks for any advice * * 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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