Hi Daniel First, newer versions of SPSS have dramatically improved their ability to do stuff with missing data - I believe it's an additional module, and in SPSS-world, each additional module = $$$.
Analyzing missing data is a 3 step process. First, you impute, creating multiple datasets, then you analyze each dataset in the conventional way, then you combine the results. There are two (that I know of) packages for imputaton - these are mi and mice. rseek.org will find them for you. Hope that helps, Jeremy On 29 June 2010 22:14, Daniel Chen <n...@pushih.com> wrote: > Hi, > > I am a long time SPSS user but new to R, so please bear with me if my > questions seem to be too basic for you guys. > > I am trying to figure out how to analyze survey data using logistic > regression with multiple imputation. > > I have a survey data of about 200,000 cases and I am trying to predict the > odds ratio of a dependent variable using 6 categorical independent variables > (dummy-coded). Approximatively 10% of the cases (~20,000) have missing data > in one or more of the independent variables. The percentage of missing > ranges from 0.01% to 10% for the independent variables. > > My current thinking is to conduct a logistic regression with multiple > imputation, but I don't know how to do it in R. I searched the web but > couldn't find instructions or examples on how to do this. Since SPSS is > hopeless with missing data, I have to learn to do this in R. I am new to R, > so I would really appreciate if someone can show me some examples or tell me > where to find resources. > > Thank you! > > Daniel > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > -- Jeremy Miles Psychology Research Methods Wiki: www.researchmethodsinpsychology.com ______________________________________________ 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.
