Fitting Linear Mixed-Effects Models Using lme4
University of Wisconsin–Madison · ETH Zurich · +1 more institution
Abstract
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the…
Citation impact
- FWCI
- 5135.22
- Percentile
- 100%
- References
- 48
Authors
4Topics & keywords
- Restricted maximum likelihood
- Deviance (statistics)
- Mixed model
- Smoothing
- Applied mathematics
- Likelihood function
- Mathematics
- Generalized linear model