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From |
Fred Wolfe <fwolfe@arthritis-research.org> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Re: Stata 11 imputation |

Date |
Mon, 27 Jul 2009 14:38:58 -0500 |

I found the following slightly more recent papers: Using Calibration to Improve Rounding in Imputation Recai M Yucel, Yulei He, Alan M Zaslavsky. The American Statistician. May 1, 2008, 62(2): 125-129. doi:10.1198/000313008X300912. Robustness of a multivariate normal approximation for imputation of incomplete binary data Coen A. Bernaards, Thomas R. Belin, Joseph L. Schafer Statistics in Medicine Volume 26 Issue 6, Pages 1368 - 1382 (2006) which seem to say its OK to round binary data if you do it correctly, though I have only seen the abstracts (don't have access to the paper from where I am). Fred Wolfe On Mon, Jul 27, 2009 at 11:31 AM, Joseph Coveney<jcoveney@bigplanet.com> wrote: > Fred Wolfe wrote: > > I have been reading the Stata 11 imputation manual. . > > The manual states (page 107), "In practice, multiple variables usually > must be imputed simultaneously, and that requires using a multivariate > imputation method. The choice of an imputation method in this case > depends on the pattern of missing values." In my instance this means > using -mi impute mvn- > > Using Royston's multivariate -ice-, it was possible to specify > mulivariate matching, oligit, mlogit, and logit. This is not possible > with -mi impute mvn -. From a users point of this means out of usual > (expected) range values (e.g., ages <0, non-integer categorical > values). The manual suggests (page 109), "For multiple categorical > variables with only two categories (binary or dummy variables), a > multivariate normal approach ([MI] mi impute mvn) can be used to > impute missing values and then round the imputed values to 0 if the > value is smaller than 0.5, or 1 otherwise. For categorical variables > with more than two categories, Allison (2001) describes how to use the > normal model to impute missing values." > > > I wonder if it might be possible in a revision of the manual to > actually describe how to impute categorical values without having to > purchase Allison's book (available on Amazon.com at a reasonable > cost). [remainder omitted] > > -------------------------------------------------------------------------------- > > These appear to give some insight as to what Paul Allison's book might be > saying. > > www2.sas.com/proceedings/sugi30/112-30.pdf > > www2.sas.com/proceedings/sugi30/113-30.pdf > > Their message now seems to be not to round at all. > > Joseph Coveney > > > > * > * 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/ > -- Fred Wolfe National Data Bank for Rheumatic Diseases Wichita, Kansas NDB Office +1 316 263 2125 Ext 0 Research Office +1 316 686 9195 fwolfe@arthritis-research.org * * 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: Stata 11 imputation***From:*Fred Wolfe <fwolfe@arthritis-research.org>

**st: Re: Stata 11 imputation***From:*"Joseph Coveney" <jcoveney@bigplanet.com>

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