[R] Imputing Missing Data: A Good Starting Point?

[David L Carlson]

You might look at Allison's short book for a quick introduction to the
issues:

Paul D. Allison. 2002. Missing Data. Sage Quantitative Applications in the
Social Sciences No. 136.

Online there is http://www.multiple-imputation.com/ which provides a
bibliography (with links to articles that are available online). 

Chapter 25 on Missing Data Imputation (Andrew Gelman and Jennifer Hill.
2006. Data Analysis Using Regression and Multilevel/Hierarchical Models.
Cambridge University Press) which is available at
http://lane.compbio.cmu.edu/courses/gelmanmissing.pdf provides examples of
several approaches and provides R code for them.

----------------------------------------------
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 Ken
Sent: Tuesday, November 01, 2011 4:48 PM
To: Sascha Vieweg
Cc: r-help at r-project.org
Subject: Re: [R] Imputing Missing Data: A Good Starting Point?

Hope this helps:
http://rss.acs.unt.edu/Rdoc/library/randomForest/html/rfImpute.html
Ken Hutchison

On Nov 1, 2554 BE, at 5:29 PM, Sascha Vieweg <saschaview at gmail.com> wrote:

> Hello
> 
> I am working on my first attempt to impute missing data of a data set with
systematically incomplete answers (school performance tests). I was googling
around for some information and found Amelia (Honaker et al., 2010) and the
mi package (Yu-Sung et al., n.d.). However, since I am new to this field, I
was wondering whether some experts could give a good recommendation of a
starting point for me, that is a point that combines theory as well as
practical examples. Of course, My primary interest is to complete the task
in time (1 week), however, I want to acquire skills for a program that
provides some future, and of course I want some background on what I am
doing (and what not). Could you help with some hints, experiences, and
recommendations?
> 
> Thank you.
> 
> Regards
> *S*
> 
> -- 
> Sascha Vieweg, saschaview at gmail.com
> 
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