Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: MI: Multiple Imputation
From
Shikha Sinha <[email protected]>
To
[email protected]
Subject
Re: st: MI: Multiple Imputation
Date
Mon, 20 Dec 2010 17:08:37 -0500
A follow-up question: How can I run the following command for each
country? Can I use bysort,
mi estimate, or: logistic Y X1 X2 edu
Thanks,
Shikha
On Mon, Dec 20, 2010 at 4:17 PM, Wesley D. Eddings, StataCorp
<[email protected]> wrote:
> Shikha Sinha <[email protected]> asked about using -mi impute mvn- to
> impute a categorical variable:
>
>> Hi,
>>
>> I am using -mi for imputing the missing values. The variable is "edu" has
>> five categories (1=primary, 2=secondary, and so on...). I used the following
>> command:
>>
>> ...
>>
>> mi impute mvn edu = i.gender age country, add (5)
>> mi estimate, or: logistic Y X1 X2 edu
>>
>> ...
>>
>> (a) Why some observations have negative values for _1_edu, _2_edu, _3_edu,
>
>
> The -mi impute mvn- command uses a multivariate normal model and treats "edu"
> as continuous, so the imputed values are not guaranteed to be positive.
> Shikha may instead use -mi impute ologit- or -mi impute mlogit-, depending on
> whether or not the categories of "edu" should be considered ordered.
>
> Shikha also asked,
>
>> (b) How do we use the five new generated variable? Can I just run
>>
>> logistic Y X1 X2 _1_edu
>>
>> or
>>
>> logistic Y X1 X2 _2_edu
>>
>> (c) Can I create a dummy for primary or secondary schooling from the imputed
>> values _1_edu?
>
>
> The five new variables _1_edu, _2_edu, ... , _5_edu are the imputed values of
> "edu" in the -wide- style for each of the five imputations. It is not
> appropriate to include the new variables directly as predictors; the
> appropriate command for a multiple-imputation analysis is -mi estimate-, as
> illustrated in Shikha's code. -mi estimate- will analyze the five imputations
> and combine them into a single multiple-imputation result.
>
> Shikha may add the i. factor-variable prefix to "edu" to include dummies for
> the imputed "edu" variable. It is not necessary to create dummies manually
> from a -mi- variable like _1_edu.
>
> We also recommend that Shikha include the variables Y, X1, and X2 in the
> imputation model. More model-building guidelines appear in the "Model
> building" section of the documentation entry -[MI] mi impute-.
>
> --Wes
> [email protected]
>
>
>
>
> *
> * 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/