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From |
"ayazh" <0ah9@qlink.queensu.ca> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Limit on imputing miss values? |

Date |
Wed, 14 May 2003 11:28:57 -0500 |

Hello Check out this article(http://www.massey.ac.nz/~wwiims/research/letters/volume3number1/ scheffer_2.pdf). It gives some guidance about which method of imputation to use for x% of data to be imputed given which missingness mechanism is present. good luck Ayaz > One alternativ is of course to assign the missing values a value > which allows them to be included in the analyses as a dummy variable. > It may be of interest to see how the other predictors perform if you > include the dummyvariables for missing values compared to if you > impute them. It would also be of interest to know if these persons > are different from the others in any way. What persons are less > willing to tell about their income? In what way may the exclusion of > them give biased results? > > Roland Andersson > > > --- In statalist@yahoogroups.com, "Sabine N. Merz" <uribazo@r...> > wrote: > > Dear All: > > > > I have a question where I simply do not know if there is a "right" > answer > > but I would much appreciate some feedback because there might be > a "golden > > rule" that I simply have overlooked. (Too much time spend dealing > with this > > would explain it.) > > > > *Is there a limit on how how many missing values one can or rather > should > > impute? > > > > In my particular case the missing values all concern the oh, so > sensitive > > personal income question. I already cross checked, e.g., with labor > force > > status, hours worked, and such but I am still left with about 7% of > my > > respondents who did not answer this question. I would not feel > uncomfortable > > imputing 1% of missing cases but 7% seems a bit much. From the > missing > > values options provided it does seem that these folks simply > refused to > > answer the question. > > > > I will likely simply use the stats "impute" option and see what I > get and > > compare these results to what would happen if I simply leave out 7% > of my > > sample. (Or would you suggest another method to deal with missing > values?) > > Still neither one is a very elegant solution. > > > > Thank you for any advice you might have. > > > > Best wishes, > > Sabine Merz > > > > > > * > > * For searches and help try: > > * http://www.stata.com/support/faqs/res/findit.html > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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