Originally, small numbers of imputations (3 or 5) were suggested, but currently 
there seems to be preference for larger numbers.
Many recent studies that do report numbers of imputation used between 20 and 
100 data sets (subjective view), but I’ve also seen as many as a thousand.
I guess that it depends on the amount of Monte Carlo error (the loss of power 
to for testing an association) you are willing to accept.
White, Royston and Wood (2010) suggest in their Statistics in Medicine journal 
article as a rule of thumb to use “at least the percentage of incomplete cases” 
(100 times the fraction of missing information), but they also state that you 
might need more in specific settings.


Adriaan W. Hoogendoorn, PhD
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Van: Impute -- Imputations in Data Analysis 
[mailto:[email protected]] Namens DAVID R JOHNSON
Verzonden: maandag 12 september 2016 0:13
Aan: [email protected]
Onderwerp: Re: Typical number of imputations

My experience is that authors who use MI seldom report the number of 
imputations they used.

------------------------------------------------------------------------------
David R. Johnson
Professor of Sociology, Human Development and Family Studies, and Demography
Department of Sociology
413 Oswald Tower
The Pennsylvania State University
University Park, PA 16802
814-865-9564
[email protected]<mailto:[email protected]>
-------------------------------------------------------------------------------

________________________________
From: "Allison, Paul D" <[email protected]<mailto:[email protected]>>
To: "Impute" 
<[email protected]<mailto:[email protected]>>
Sent: Saturday, September 10, 2016 7:58:55 AM
Subject: Re: Typical number of imputations


Good question, but I'm not aware of any studies.




Paul D. Allison, Professor
Department of Sociology
University of Pennsylvania
581 McNeil Building
3718 Locust Walk
Philadelphia, PA 19104-6299
610-715-5702
419-818-1220 (fax)
www.pauldallison.com<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.pauldallison.com_&d=CwMFAw&c=yHlS04HhBraes5BQ9ueu5zKhE7rtNXt_d012z2PA6ws&r=N9mDDDuK1isnKK-Q36bwNuZl066Rn4cNQtKxtVKMnWBnZ5yXlXHty3gF6wWXsdE6&m=WZhkIrvV_nPE4MPWJCbcERwh_uwCepoMW9A1CIlGono&s=jhCMas8sQAOyoeHxUbvqK4sCPETcmNiEkxGRSgzeBj8&e=>

________________________________
From: Impute -- Imputations in Data Analysis 
<[email protected]<mailto:[email protected]>>
 on behalf of Paul von Hippel 
<[email protected]<mailto:[email protected]>>
Sent: Friday, September 9, 2016 11:05 PM
To: 
[email protected]<mailto:[email protected]>
Subject: Typical number of imputations

Are there studies documenting how many imputations analysts typically use in 
MI? I know the recommendations, but I'm interested in what users are actually 
doing -- and whether users are using more imputations now than previously.

Best wishes,
Paul von Hippel
LBJ School of Public Affairs
Sid Richardson Hall 3.251
University of Texas, Austin
2315 Red River, Box Y
Austin, TX  78712


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