Package: mmrm 0.3.12.9000

Daniel Sabanes Bove

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], 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]

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mmrm.pdf |mmrm.html
mmrm/json (API)
NEWS

# Install 'mmrm' in R:
install.packages('mmrm', repos = c('https://openpharma.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/openpharma/mmrm/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

17 exports 122 stars 5.20 score 44 dependencies 4 dependents 101 scripts 2.9k downloads

Last updated 4 days agofrom:0bc1417e65. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 14 2024
R-4.5-win-x86_64OKSep 14 2024
R-4.5-linux-x86_64OKSep 14 2024
R-4.4-win-x86_64OKSep 14 2024
R-4.4-mac-x86_64OKSep 14 2024
R-4.4-mac-aarch64OKSep 14 2024
R-4.3-win-x86_64OKSep 14 2024
R-4.3-mac-x86_64OKSep 14 2024
R-4.3-mac-aarch64OKSep 14 2024

Exports:as.cov_structaugmentcomponentcov_structcov_typesdf_1ddf_mdemp_startfit_mmrmfit_single_optimizerglancemmrmmmrm_controlrefit_multiple_optimizersstd_starttidyVarCorr

Dependencies:backportsbriocallrcheckmateclicrayondescdiffobjdigestevaluatefansifsgenericsgluejsonlitelatticelifecyclemagrittrMatrixnlmepillarpkgbuildpkgconfigpkgloadpraiseprocessxpsR6rbibutilsRcppRcppEigenRdpackrematch2rlangrprojrootstringistringrtestthattibbleTMButf8vctrswaldowithr

Between-Within

Rendered frombetween_within.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2023-10-25
Started: 2023-08-23

Coefficients Covariance Matrix Adjustment

Rendered fromcoef_vcov.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-01-10
Started: 2023-02-02

Comparison with other software

Rendered frommmrm_review_methods.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2023-12-19
Started: 2023-05-06

Covariance Structures

Rendered fromcovariance.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2023-10-25
Started: 2022-07-04

Details of Hypothesis Testing

Rendered fromhypothesis_testing.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-01-16
Started: 2023-12-22

Details of Weighted Least Square Empirical Covariance

Rendered fromempirical_wls.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-04-03
Started: 2023-03-16

Kenward-Roger

Rendered fromkenward.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2023-10-25
Started: 2022-12-09

Mixed Models for Repeated Measures

Rendered frommethodological_introduction.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2023-10-25
Started: 2023-02-02

Model Fitting Algorithm

Rendered fromalgorithm.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-01-10
Started: 2022-06-30

Package Introduction

Rendered fromintroduction.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-01-10
Started: 2022-04-28

Package Structure

Rendered frompackage_structure.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-01-10
Started: 2022-10-10

Prediction and Simulation

Rendered frompredict.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2024-01-10
Started: 2023-06-06

Satterthwaite

Rendered fromsatterthwaite.Rmdusingknitr::rmarkdownon Sep 14 2024.

Last update: 2023-10-25
Started: 2022-12-16

Readme and manuals

Help Manual

Help pageTopics
'mmrm' Packagemmrm-package
Coerce into a Covariance Structure Definitionas.cov_struct as.cov_struct.formula
Example Data on BCVAbcva_data
Component Access for 'mmrm_tmb' Objectscomponent
Define a Covariance Structurecov_struct
Covariance Typescovariance_types cov_types
Calculation of Degrees of Freedom for One-Dimensional Contrastdf_1d
Calculation of Degrees of Freedom for Multi-Dimensional Contrastdf_md
Support for 'emmeans'emmeans_support
Empirical Starting Valueemp_start
Example Data on FEV1fev_data
Low-Level Fitting Function for MMRMfit_mmrm
Fitting an MMRM with Single Optimizerfit_single_optimizer
Format Covariance Structure Objectformat.cov_struct
Fit an MMRMmmrm
Control Parameters for Fitting an MMRMmmrm_control
Tidying Methods for 'mmrm' Objectsaugment.mmrm glance.mmrm mmrm_tidiers tidy.mmrm
Methods for 'mmrm_tmb' ObjectsAIC.mmrm_tmb BIC.mmrm_tmb coef.mmrm_tmb deviance.mmrm_tmb fitted.mmrm_tmb formula.mmrm_tmb logLik.mmrm_tmb mmrm_tmb_methods model.frame.mmrm_tmb model.matrix.mmrm_tmb predict.mmrm_tmb print.mmrm_tmb residuals.mmrm_tmb simulate.mmrm_tmb terms.mmrm_tmb VarCorr VarCorr.mmrm_tmb vcov.mmrm_tmb
Print a Covariance Structure Objectprint.cov_struct
Refitting MMRM with Multiple Optimizersrefit_multiple_optimizers
Standard Starting Valuestd_start