Package: mmrm 0.3.17.9000

mmrm: Mixed Models for Repeated Measures

Mixed models for repeated measures (MMRM) are a popular choice for analyzing longitudinal continuous outcomes in randomized clinical trials and beyond; see Cnaan, Laird and Slasor (1997) <doi:10.1002/(SICI)1097-0258(19971030)16:20%3C2349::AID-SIM667%3E3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) <doi:10.1177/009286150804200402> for a review. This package implements MMRM based on the marginal linear model without random effects using Template Model Builder ('TMB') which enables fast and robust model fitting. Users can specify a variety of covariance matrices, weight observations, fit models with restricted or standard maximum likelihood inference, perform hypothesis testing with Satterthwaite or Kenward-Roger adjustment, and extract least square means estimates by using 'emmeans'.

Authors:Daniel Sabanes Bove [aut, cre], Liming Li [aut], Julia Dedic [aut], Doug Kelkhoff [aut], Kevin Kunzmann [aut], Brian Matthew Lang [aut], Christian Stock [aut], Ya Wang [aut], Craig Gower-Page [ctb], Dan James [aut], Jonathan Sidi [aut], Daniel Leibovitz [aut], Daniel D. Sjoberg [aut], Nikolas Ivan Krieger [aut], Lukas A. Widmer [ctb], Boehringer Ingelheim Ltd. [cph, fnd], Gilead Sciences, Inc. [cph, fnd], F. Hoffmann-La Roche AG [cph, fnd], Merck Sharp & Dohme, Inc. [cph, fnd], AstraZeneca plc [cph, fnd], inferential.biostatistics GmbH [cph, fnd]