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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", "0.3.11")



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: 2024-03-05
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 0.3.11, https://cran.r-project.org/web/packages/mmrm
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)
Other packages that cited mmrm R package
View mmrm citation profile
Other R packages that mmrm depends, imports, suggests or enhances
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
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