Check out the book Linear Mixed Models: A Practical Guide Using Statistical Software by Brady West.
It sets up analyses, similar to ones you described, in SPSS, R, and others as well. In general, I think it is good to know a couple of different packages, especially if you plan on doing a lot of data analysis and data manipulation. On Sun, Jan 31, 2010 at 11:24 PM, Anton du Toit <atdutoitrh...@gmail.com> wrote: > Dear R-helpers, > > I’m writing for advice on whether I should use R or a different package or > language. I’ve looked through the R-help archives, some manuals, and some > other sites as well, and I haven’t done too well finding relevant info, > hence my question here. > > I’m working with hierarchical data (in SPSS lingo). That is, for each case > (person) I read in three types of (medical) record: > > 1. demographic data: name, age, sex, address, etc > > 2. ‘admissions’ data: this generally repeats, so I will have 20 or so > variables relating to their first hospital admission, then the same 20 again > for their second admission, and so on > > 3. ‘collections’ data, about 100 variables containing the results of a > battery of standard tests. These are administered at intervals and so this > is repeating data as well. > > The number of repetitions varies between cases, so in its one case per line > format the data is non-rectangular. > > At present I have shoehorned all of this into SPSS, with each case on one > line. My test database has 2,500 variables and 1,500 cases (or persons), and > in SPSS’s *.SAV format is ~4MB. The one I finally work with will be larger > again, though likely within one order of magnitude. Down the track, funding > permitting, I hope to be working with tens of thousands of cases. > > I am wondering if I should keep using SPSS, or try something else. > > The types of analysis I’ll typically will have to do will involve comparing > measurements at different times, e.g. before/ after treatment. I’ll also > need to compare groups of people, e.g. treatment / no treatment. Regression > and factor analyses will doubtless come into it at some point too. > > So: > > 1. should I use R or try something else? > > 2. can anyone advise me on using R with the type of data I’ve described? > > > Many thanks, > > Anton du Toit > > [[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. > > ______________________________________________ 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.