[R] Hierarchical data sets: which software to use?
juliet.hannah at gmail.com
Fri Feb 5 02:29:20 CET 2010
Check out the book
Linear Mixed Models: A Practical Guide Using Statistical Software by
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,
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 <atdutoitrhelp at 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.
> 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
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