I am an R newbie trying to use LME for HLM. I have a number of individual variables (Ind) nested within neighborhoods, for which I have a number of characteristics (Ngb). I want to model the simultaneous effects of the Ngb characteristics and Ind predictors on an outcome, X. The data is in a data frame that looks something like this (using made up values for example)... Ngb# Ngb1 Ngb2...Ind1 Ind2...OutcomeX 1 .10 .05 0 2 46 1 .10 .05 1 5 47 1 .10 .05 1 4 46 2 .12 .07 0 3 44 2 .12 .07 1 6 44 2 .12 .07 0 7 48 3 .14 .04 1 4 45 3 .14 .04 1 2 42 3 .14 .04 0 3 46 In addition to the typical regression results (Coefficients, SE, R^2), I want to see the individual level error variance and the neighborhood level error variance. In all, I have about 5 neighborhood level variables and perhaps 8-10 individual level variables. Can somone tell me how I would specify this model in R using LME to get the info that I want? Thanks Four Your Help Brett Magill -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._