Repeated measures for unbalanced data in R
Hi Manuel, It's not quite clear from your question whether you are asking for help choosing a statistical model IN GENERAL (not really the purpose of this list, but sometimes people help out anyway) or whether you have a specific model in mind and are askig for help RUNNING IT (in which case, you should tell us what the model is, and mention what you're tried). Regarding the MODEL question, it is not clear whether COUNTRY is random (you're not looking for differences among countries, rather, you're sampling countries and trying to tell whether there's a trend over time, so you probably want lmer(rate ~ year + (1|country), data=?) ...) or if YEAR is random (you're trying to look at differences among countries, so you probably want lmer(rate ~ country + (1|year), data=?) ...), though you may be empirically underidentified in the latter case. ...or maybe you want something else entirely. In any case, being as precise as you can be about what you want to do and what the question is (i.e., "model help" or "method help" or "function help"), you may get better responses on R-help lists (ME and Ecology, though I only read ME). --Adam
On Wed, 16 Sep 2009, Manuel Sp?nola wrote:
Dear list members, Sorry for crossposting but I posted the following message to the R-SIG-Ecology and I did not have many answers. I would like to run a repeated measure model in R and I would like to have your advice on how to parameterize the model and which package and function should I use.. I have: Response variable: Disease rate (number of cases x 1000 people) County (16 counties, it would be the subject) Year: from 2002 to 2007 My data set is unbalanced (the counties do not have information for all the years). Thank you very much in advance. Best, Manuel Sp?nola -- Manuel Sp?nola, Ph.D. Instituto Internacional en Conservaci?n y Manejo de Vida Silvestre Universidad Nacional Apartado 1350-3000 Heredia COSTA RICA mspinola at una.ac.cr mspinola10 at gamil.com Tel?fono: (506) 2277-3598 Fax: (506) 2237-7036
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