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From |
Leslie Phillips <leslie.phillips@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: ICE: Combining proportions using Rubin's rules via mim |

Date |
Sat, 1 Jan 2011 10:53:02 -0800 |

Dear all, I am using Patrick Royston's ICE to multiply impute data that will be used to calculate proportions. I have calculated my proportions on the m imputed datasets which ICE appends into one dataset. I now want to combine my proportions using Rubin's rule. It is my first experience with MICE/ICE and I am a basic to less-than-basic Stata user so I am stumbling through this a bit but my read of it is that the overall estimate is the average of the individual estimates (in my case proportions). It seems ICE will do this for me as follows: 1) I use ice to carry out m imputations 2) I calculate my proportion ("myprop") in the appended dataset which calculates m proportions for each _mi 3) Here's where it gets tricky for me, is it correct to use the mim combine command as below to get the appropriately combined proportions and a standard error that accounts for both the within and between imputation variance a la Rubin? And if so, I should just repeat this for each _mi? mim, cat(combine) est(_b[myprop]) se(_se[myprop]) : mean myprop if _mi==1 Applying Rubin's rules, using statsby for analysis: -> statsby est = (_b[myprop]) se = (_se[myprop]), by(_mj) nodots clear : mean myprop if _mi==1 command: mean myprop if _mi==1 est: _b[myprop] se: _se[myprop] by: _mj Combined estimate | Mean Std. Err. [95% Conf. Interval] FMI -------------------+---------------------------------------------------------- _b[myprop] | .7146546 .0178508 .637849 .7914602 . Any guidance is warmly welcomed, Leslie leslie.phillips@gmail.com University of Washington, Seattle * * 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/

**Follow-Ups**:**Re: st: ICE: Combining proportions using Rubin's rules via mim***From:*Stas Kolenikov <skolenik@gmail.com>

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