Hi Glenys, I would start by reading the Zelig mi() help file. Best, Anders On Mon, 15 Oct 2007, Glenys Lafrance wrote: - Amelia mailing list served by Harvard-MIT Data Center [Un]Subscribe/View Archive: http://lists.gking.harvard.edu/?info=amelia

Hello Glenys, Once you have the .csv files, it is relatively easy to put them into Zelig. The quickest way is a bit of hack, but it works. #### begin code #### library(Zelig) m <- 5 # number of imputations imp.data <- list() # where we store the datasets for (i in 1:m) { file.name <- paste("outdata",i,".csv",sep="") #where "outdata" is the root of the filename imp.data[[i]] <- read.csv(file=file.name) } class(imp.data) <- c("mi","list") zelig(formula=y~x, model=foo, data=imp.data) ##### end code ##### this code loops through each filename and makes a list of $m$ datasets, where $m$ is the number of imputations you ran. Zelig has a slightly awkward way of bringing those datasets together (you have to list them one by one), so line with "class(imp.data)" makes the list proper for Zelig. now you can feed it to the "zelig" function along with your formula and model and it should report back combined estimates for all your quantities of interest. I hope that was clear. If you have any question, feel free to get back to the list. Or if anyone has a cleaner way of implementing the same thing, please let us know. Thanks, matt. On 10/15/07, Glenys Lafrance &lt;glenys.lafrance(a)sympatico.ca&gt; wrote: - Amelia mailing list served by Harvard-MIT Data Center [Un]Subscribe/View Archive: http://lists.gking.harvard.edu/?info=amelia