© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The linear mixed model, sometimes referred to as the multi-level model, is one of the most widely used tools for analyses involving clustered data. Various definitions of R 2 have been proposed for the linear mixed model, but several limitations prevail. Presently, there is no method to compute R 2 for the linear mixed model that accommodates an interpretation based on variance partitioning, a method to quantify uncertainty and produce confidence limits for the R 2 statistic, and a capacity to use the R 2 statistic to conduct covariance model selection in a manner similar to information criteria. In this article, we introduce such an R 2 statistic. The proposed R 2 measures the proportion of generalized variance explained by fixed effects in the linear mixed model. Simulated and real longitudinal data are used to illustrate the statistical properties of the proposed R 2 and its capacity to be applied to covariance model selection.