Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down on April 23, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: Re: Re: Re: st: Situation where multiple imputation may be of no use?


From   Clyde B Schechter <clyde.schechter@einstein.yu.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: Re: Re: Re: st: Situation where multiple imputation may be of no use?
Date   Fri, 17 Feb 2012 15:32:10 +0000

Belated but profound thanks to Stas Kolenikov and Maarten Buis for their further thoughts on my question.

Stas--my MNAR simulations were precisely the two situations you describe (well, the effect size I chose was a bit smaller, reflecting what I expect in my proposed study).  And they do indeed show that with missing data only in the dependent variable, neither MI nor FIML leads to any improvement in statistical power, nor do they correct bias at all.

Maarten--what an elegant application of Bayes' theorem.  Wish I had thought of it.  It puts my remaining doubts about this to rest.

Clyde Schechter
Dept. of Family & Social Medicine
Albert Einstein College of Medicine
Bronx, NY, USA



*
*   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/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index