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From |
Andrea Bennett <mac.stata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Degrees of Freedom, F-test and Multiple Imputation |

Date |
Wed, 2 Nov 2011 13:40:30 +0100 |

Hi! I am slightly confused with the degrees of freedom in regressions based on imputed data (M=20). Let's say I have 50 school classes nested in 30 schools. Assume a regression that is based on a single imputed data set (e.g. m=5) and clustered on the class-level. Now, adding fixed effects for schools shows that the F-test has not enough degrees of freedom to be calculated. However, running the same regression with the full set of imputed data (m=0, …, m=20) is - according to Stata - no problem since the degrees of freedom are calculated over the full range of all imputed observations. My question: Can I belief these Stata calculations? I don't quite understand why I should have more degrees of freedom and whether I can make use of it, i.e. would it be statistically ok to include fixed effects in the above case when working with the complete set of imputed data (m=0, …, m=20) since Stata reports the F-test just fine? Your suggestions are very welcomed! Andrea * * 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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