Repeated Measurement Models for Discrete Times

Companion R package for the course "Statistical analysis of correlated and repeated measurements for health science researchers" taught by the section of Biostatistics of the University of Copenhagen. It implements linear mixed models where the model for the variance-covariance of the residuals is specified via patterns (compound symmetry, toeplitz, unstructured, ...). Statistical inference for mean, variance, and correlation parameters is performed based on the observed information and a Satterthwaite approximation of the degrees of freedom. Normalized residuals are provided to assess model misspecification. Statistical inference can be performed for arbitrary linear or non-linear combination(s) of model coefficients. Predictions can be computed conditional to covariates only or also to outcome values.


Reference manual

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install.packages("LMMstar")

1.1.0 by Brice Ozenne, 2 years ago


https://github.com/bozenne/LMMstar


Report a bug at https://github.com/bozenne/LMMstar/issues


Browse source code at https://github.com/cran/LMMstar


Authors: Brice Ozenne [aut, cre] , Julie Forman [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports copula, doParallel, foreach, ggplot2, grid, lava, Matrix, multcomp, nlme, numDeriv, parallel, rlang

Suggests asht, data.table, ggh4x, ggpubr, lattice, mvtnorm, lme4, lmerTest, mice, nlmeU, optimx, pbapply, psych, Publish, qqtest, R.rsp, reshape2, rmcorr, scales, testthat


See at CRAN