multilevel nested data in lmer models
On 2/15/07, Hallstrom, Wayne (Calgary)
<Wayne.Hallstrom at worleyparsons.com> wrote:
I have what should be a simple question about structure of the formula for an lmer model. However, I can find no detailed description of how to write multilevel nested formulas for lmer though so I need some advice. Count data were collected at 10 subsample locations nested within each of 7 general locations over a 20 year period of repeated measures. At each of the 7 general locations there was a treatment applied partway through the 20 year period to 1/2 of the subsample locations. I thought running the lmer routine with the following general formula setup would account for the fixed effects of the treatment and the random effects of the nesting structure. A Quasipoisson distribution was used to account for over/underdispersed data. model1 <- lmer(count ~ a + (1 | b / c), dataset) This model returns an error message though - "too many groups, only the first is used". I thought this formula should account for the grouped and nested data structure. I have used this model structure with a different dataset and a similar lmer model and it worked fine, nesting the one explanatory variable within the other in the proper arrangement and producing reasonable results. This time it does not work. Is there a different way the formula should be set up?
Could you show us the structure of the data set (use str(dataset) and a transcript of your attempt to fit the model? The reason I ask is because I don't think that error message occurs in the lme4 package. I just did a quick check on both the R and the C sources and I can't find it. Also please include the output of sessionInfo() in your message so we know what versions of various packages you are using.
Someone with more background in this method must have had a similar
problem before while using this lmer routine, so hopefully another
perosn on the list can describe/advise how to deal with this kind of
nested data and what may be the problem here...
Thank you,
Wayne Hallstrom
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