This is chopped off. What happens next is important. EM can be used to compute covariance matrices and conducts the statistical analysis without imputing any missing values or it can be used to impute missing values to create one or multiple data sets.
You might find Missing Data by Paul D. Allison to be useful. ---------------------------------------------- David L Carlson Associate Professor of Anthropology Texas A&M University College Station, TX 77843-4352 > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > project.org] On Behalf Of ya > Sent: Sunday, July 22, 2012 5:11 AM > To: r-help > Subject: Re: [R] EM for missing data > > hi Greg, David, and Tal, > > Thank you very much for the information. > > I found this in SPSS 17.0 missing value manual: > > EM Method > > This method assumes a distribution for the partially missing data and > bases inferences > on the likelihood under that distribution. Each iteration consists of > an E step and an > M step. The E step finds the conditional expectation of the b ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
