Transcription of Fitting Linear Mixed-Effects Models using lme4
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Fitting Linear Mixed-Effects Models using lme4
Fitting Linear Mixed-Effects Models using lme4 Douglas BatesUniversity of Wisconsin-MadisonMartin M chlerETH ZurichBenjamin M. BolkerMcMaster UniversitySteven C. WalkerMcMaster UniversityAbstractMaximum likelihood or restricted maximum likelihood (REML) estimates of the pa-rameters in Linear Mixed-Effects Models can be determined using thelmerfunction in thelme4package forR. As for most model - Fitting functions inR, the model is described inanlmercall by a formula, in this case including both fixed- and random-effects formula and data together determine a numerical representation of the model fromwhich the profiled deviance or the profiled REML criterion can be evaluated as a functionof some of the model parameters.
paper we describe the formulation and representation of linear mixed models. The techniques used for generalized linear and nonlinear mixed models will be described separately, in a future paper. At present, the main alternative to lme4 for mixed modeling in R is the nlme package (Pin-heiro, Bates, DebRoy, Sarkar, and R Core Team 2014).
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