Linear mixed-effects models using R : a step-by-step approach - Ga$1!8r(Bi, Andrzej T.s; Burzykowski, Tomasz (New York, NY : Springer, 2013)
Introduction -- Introduction -- Case Studies -- Data Exploration -- Linear Models for Independent Observations -- Linear Models with Homogeneous Variance -- Fitting Linear Models with Homogeneous Variance: The lm() and gls() Functions -- ARMD Trial: Linear Model with Homogeneous Variance -- Linear Models with Heterogeneous Variance -- Fitting Linear Models with Heterogeneous Variance: The gls() Function -- ARMD Trial: Linear Model with Heterogeneous Variance -- Linear Fixed-effects Models for Correlated Data -- Linear Model with Fixed Effects and Correlated Errors -- Fitting Linear Models with Fixed Effects and Correlated Errors: The gls() Function -- ARMD Trial: Modeling Correlated Errors for Visual Acuity -- Linear Mixed-effects Models -- Linear Mixed-Effects Model -- Fitting Linear Mixed-Effects Models: The lme()Function -- Fitting Linear Mixed-Effects Models: The lmer() Function -- ARMD Trial: Modeling Visual Acuity -- PRT Trial: Modeling Muscle Fiber Specific-Force -- SII Project: Modeling Gains in Mathematics Achievement-Scores -- FCAT Study: Modeling Attainment-Target Scores -- Extensions of the RTools for Linear Mixed-Effects Models.
Includes bibliographical references and indexes.
Keywords: Linear models (Statistics); R (Computer program language)