[R] Can lmer() fit a multilevel model embedded in a regression?

[Andrew Gelman]

Ronggui,

Thanks for the pointer. I am aware of this Rnews article and in fact
have used lmer() to fit non-nested grouping factors. The difficulty here
is that the second level--foods--is not a grouping factor at all.

Andrew

ronggui wrote:

> I don't answser your question directly.I juset point out that Rnews
> 2005-1 has an article about lmer :Fitting linear mixed models in R
> Using the lme4 package by the author of the package Matrix.The article
> says "lmer handles nested and non-nested grouping factors
> equally easily". Hope This helps.
>
> 2006/5/20, Andrew Gelman <gelman at stat.columbia.edu>:
>
>> I would like to fit a hierarchical regression model from Witte et al.
>> (1994; see reference below). It's a logistic regression of a health
>> outcome on quntities of food intake; the linear predictor has the form,
>> X*beta + W*gamma,
>> where X is a matrix of consumption of 82 foods (i.e., the rows of X
>> represent people in the study, the columns represent different foods,
>> and X_ij is the amount of food j eaten by person i); and W is a matrix
>> of some other predictors (sex, age, ...).
>>
>> The second stage of the model is a regression of X on some food-level
>> predictors.
>>
>> Is it possible to fit this model in (the current version of) lmer()?
>> The challenge is that the persons are _not_ nested within food items, so
>> it is not a simple multilevel structure.
>>
>> We're planning to write a Gibbs sampler and fit the model directly, but
>> it would be convenient to be able to flt in lmer() as well to check.
>>
>> Andrew 
>

-- 
Andrew Gelman
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Professor, Department of Political Science
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www.stat.columbia.edu/~gelman

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