[R] combined EM dataset for missing data?

David L Carlson dcarlson at tamu.edu
Sat Jul 21 21:19:52 CEST 2012

It is not clear what you actually want. Do you want to save imputed data
sets for further analysis? That is pretty simple. What do you mean by
combining the data sets? Are you confusing single imputation with multiple
imputation? In addition to the packages you mentioned, there are many
others. See the Official Statistics & Survey Methodology Task View:


David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77843-4352

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of ya
> Sent: Saturday, July 21, 2012 6:59 AM
> To: r-help
> Subject: [R] combined EM dataset for missing data?
> Hi list,
> I am wondering if there is a way to use EM algorithm to handle missing
> data and get a completed data set in R?
> I usually do it in SPSS because EM in SPSS kind of "fill in" the
> estimated value for the missing data, and then the completed dataset
> can be saved and used for further analysis. But I have not found a way
> to get the a completed data set like this in R or SAS. With Amelia or
> MICE, the missing data set were imputed a couple of times, and the new
> imputed datasets were not combined. I understand that the parameter
> estimation can still be done in the way of combination of estimates
> from each imputed data set, but it would be more convenient to have a
> combined dataset to do some analysis, for example, ANOVA with IVs
> having more than two categories. In this case, the only way to get the
> main effect of the whole IV is to estimate parameters in a single data
> set(as far as I know). If the separated imputed data sets were used,
> then the main effect showed in the result were for each category of the
> IV, respectively. I figured sometimes the readers and reviewers would
> like to see how bi!
>  g the effect for the whole IV instead of the effect of each category
> of that IV.
> This is one of the reasons I can not fully move to R from SPSS. So any
> suggestions?
> Thank you very much.
> ya
> 	[[alternative HTML version deleted]]
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