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From |
Clara Barata <maria_barata@mail.harvard.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: MI estimate, data missing in grouping variable (Stata 11) |

Date |
Thu, 5 Nov 2009 20:21:45 -0500 |

Hi all, I didn't hear from anybody in the list-serve about this issue, so I am wondering whether 1. it's a silly question, 2. my problem is not stated clearly; 3. the email didn't go through. If there's anybody out there experiencing similar problems with MI, please email me. Thanks and I apologize for the double posting, Clara On Wed, Nov 4, 2009 at 10:39 AM, Clara Barata <maria_barata@mail.harvard.edu> wrote: > Hi! > I am using the new MI software in Stata 11 and I am running into some > problems with the estimation commands. I was wondering if anybody had > any ideas on how to get around the specific problem of imputing a > variable with a lot of data missing which you will later use as a > grouping variable in your estimation models. > > let me explain this better. For my analysis I fit a ton of models by > income quintiles. However, I have a lot of data missing for income, > and so I imputted the dataset using MI creating 40 complete datasets. > For each of the datasets MI has substituted the missing value for > income with a possible value. The problem is that when I fit models > for different quintiles, Mi estimate clearly recognizes that the > estimation sample varies from one imputed dataset to another, as > follows: > > . mi estimate : regress outcome predictor predictor2 if income<= XXX > estimation sample varies between m=1 and m=2 > > To make the model work I asked MI to ignore the variation across > estimation samples by using esampvaryok. However, to make matters > worse, I then need to add fixed effects to deal with the clustering of > my data, and then MI can't fit the model at all because different > samples include different fixed effects. > > . mi estimate : regress outcome predictor predictor2 FE1-FE100 if income<= XXX > > mi estimate: omitted terms vary > The set of omitted variables or categories is not consistent > between m=1 and m=2; this is not allowed. To identify varying sets, > you can use mi xeq to run the command on individual imputations > or you can reissue the command with mi estimate, noisily > > Any ideas on how to deal with this problem? > Clara > * > * 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/ > * * 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/

**References**:**st: MI estimate, data missing in grouping variable (Stata 11)***From:*Clara Barata <maria_barata@mail.harvard.edu>

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