Have you consulted the book Pinhiero and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer)? I was able to use lme successfully only after reading the first few chapters of this book and working through the examples therein. I have not used nlme, but if I wanted to use it, I would start with this book.
hope this helps. spencer graves
[EMAIL PROTECTED] wrote:
Dear all,
I have the following question. I have to fit the hierarchical model for the hypothesis concern the individual-level effects by controlling for the individual -level attributes and national-level contextual effects on individuals by using R.
O have to obtain the estimates of the impact of the second-level (national: GDP per capita) effects on individuals ( in this instance the impact of the GDP per capita on the attitudes towards the EU enlargement) by allowing national differences in both slopes (GDP per capita) and interceps.
In R programm for the fitting the hierarchical models i can use the nlme package. I found a literature (Bryk and Raudenbush) for the hierarchical models and understood how to build this models by using the survey data. The question arise if I´m thinking about the combination of the datasets: the GDP per capita that will be hold as a constant and the survey data for each respondent.
My question is how I could solve this problem and merge the data in such a form that should be appropriate for the hieararchical regression model.
Thank a lot in advance for the help,
Silika Tereshchenko
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