Other packages > Find by keyword >

mmrm  

Mixed Models for Repeated Measures
View on CRAN: Click here


Download and install mmrm package within the R console
Install from CRAN:
install.packages("mmrm")

Install from Github:
library("remotes")
install_github("cran/mmrm")

Install by package version:
library("remotes")
install_version("mmrm", "0.3.17")



Attach the package and use:
library("mmrm")
Maintained by
Daniel Sabanes Bove
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-18
Latest Update: 2025-06-10
Description:
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) for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) 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'.
How to cite:
Daniel Sabanes Bove (2022). mmrm: Mixed Models for Repeated Measures. R package version 0.3.17, https://cran.r-project.org/web/packages/mmrm. Accessed 05 Mar. 2026.
Previous versions and publish date:
0.1.3 (2022-10-18 08:40), 0.1.5 (2022-10-18 14:12), 0.2.2 (2022-12-20 10:50), 0.3.6 (2023-11-17 21:10), 0.3.7 (2023-12-09 01:40), 0.3.8 (2024-01-24 17:40), 0.3.9 (2024-01-25 23:40), 0.3.10 (2024-01-26 13:10), 0.3.11 (2024-03-05 09:10), 0.3.12 (2024-06-26 17:00), 0.3.13 (2024-09-23 08:50), 0.3.14 (2024-09-28 01:30), 0.3.15 (2025-06-10 12:50), 0.3.16 (2025-12-09 16:20)
Other packages that cited mmrm R package
View mmrm citation profile
Other R packages that mmrm depends, imports, suggests or enhances
Complete documentation for mmrm
Functions, R codes and Examples using the mmrm R package
Some associated functions: Anova.mmrm . COV_TYPES . as.cov_struct . bcva_data . cached_mmrm_results . car_add_mmrm . check_package_version . component . cov_struct . cov_type_abbr . cov_type_name . covariance_types . df_1d . df_md . drop_elements . emit_tidymodels_register_msg . emmeans_support . emp_start . fev_data . fill_names . fit_mmrm . fit_single_optimizer . flat_expr . format.cov_struct . format_symbols . formula_rhs . h_add_covariance_terms . h_add_terms . h_coef_table . h_confirm_large_levels . h_construct_model_frame_inputs . h_default_value . h_df_1d_bw . h_df_1d_kr . h_df_1d_res . h_df_1d_sat . h_df_bw_calc . h_df_md_bw . h_df_md_from_1d . h_df_md_kr . h_df_md_res . h_df_md_sat . h_df_min_bw . h_df_to_tibble . h_drop_covariance_terms . h_extract_covariance_terms . h_factor_ref . h_get_contrast . h_get_cov_default . h_get_empirical . h_get_kr_comp . h_get_optimizers . h_get_prediction . h_get_prediction_variance . h_get_sim_per_subj . h_get_theta_from_cov . h_gradient . h_jac_list . h_kr_df . h_md_denom_df . h_mmrm_tmb_assert_start . h_mmrm_tmb_check_conv . h_mmrm_tmb_data . h_mmrm_tmb_extract_cov . h_mmrm_tmb_fit . h_mmrm_tmb_formula_parts . h_mmrm_tmb_parameters . h_newdata_add_pred . h_optimizer_fun . h_partial_fun_args . h_print_aic_list . h_print_call . h_print_cov . h_quad_form . h_reconcile_cov_struct . h_record_all_output . h_register_s3 . h_residuals_normalized . h_residuals_pearson . h_residuals_response . h_split_control . h_summarize_all_fits . h_tbl_confint_terms . h_test_1d . h_test_md . h_tr . h_valid_formula . h_var_adj . h_warn_na_action . h_within_or_between . is_infix . mmrm-package . mmrm . mmrm_control . mmrm_methods . mmrm_tidiers . mmrm_tmb_methods . parsnip_add_mmrm . position_symbol . print.cov_struct . reexports . refit_multiple_optimizers . register_on_load . std_start . tmb_cov_type . validate_cov_struct . 
Some associated R codes: between-within.R . catch-routine-registration.R . component.R . cov_struct.R . data.R . empirical.R . fit.R . interop-car.R . interop-emmeans.R . interop-parsnip.R . kenwardroger.R . mmrm-methods.R . mmrm-package.R . residual.R . satterthwaite.R . skipping.R . testing.R . tidiers.R . tmb-methods.R . tmb.R . utils-formula.R . utils-nse.R . utils.R . zzz.R .  Full mmrm package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

imagefx  
Extract Features from Images
Synthesize images into characteristic features for time-series analysis or machine learning applicat ...
Download / Learn more Package Citations See dependency  
ClimClass  
Climate Classification According to Several Indices
Classification of climate according to Koeppen - Geiger, of aridity indices, of continentality indi ...
Download / Learn more Package Citations See dependency  
roccv  
ROC for Cross Validation Results
Cross validate large genetic data while specifying clinical variables that should always be in the m ...
Download / Learn more Package Citations See dependency  
diffIRT  
Diffusion IRT Models for Response and Response Time Data
Package to fit diffusion-based IRT models to response and response time data. Models are fit using ...
Download / Learn more Package Citations See dependency  
pinp  
'pinp' is not 'PNAS'
A 'PNAS'-alike style for 'rmarkdown', derived from the 'Proceedings of the National Academy of Scie ...
Download / Learn more Package Citations See dependency  
neat  
Efficient Network Enrichment Analysis Test
Includes functions and examples to compute NEAT, the Network Enrichment Analysis Test described in ...
Download / Learn more Package Citations See dependency  

26,264

R Packages

223,360

Dependencies

70,244

Author Associations

26,265

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA