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 <[EMAIL PROTECTED]>: > >> 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 Professor, Department of Statistics Professor, Department of Political Science [EMAIL PROTECTED] www.stat.columbia.edu/~gelman Statistics department office: Social Work Bldg (Amsterdam Ave at 122 St), Room 1016 212-851-2142 Political Science department office: International Affairs Bldg (Amsterdam Ave at 118 St), Room 731 212-854-7075 Mailing address: 1255 Amsterdam Ave, Room 1016 Columbia University New York, NY 10027-5904 212-851-2142 (fax) 212-851-2164
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