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mmrm (version 0.3.16)

Mixed Models for Repeated Measures

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'.

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Install

install.packages('mmrm')

Monthly Downloads

6,214

Version

0.3.16

License

Apache License 2.0

Maintainer

Daniel Sabanes Bove

Last Published

December 9th, 2025

Functions in mmrm (0.3.16)

emit_tidymodels_register_msg

Format a Message to Emit When Tidymodels is Loaded

Empirical Starting Value

emmeans_support

Support for emmeans

Calculation of Degrees of Freedom for Multi-Dimensional Contrast

Format Symbol Objects

h_add_covariance_terms

Add Individual Covariance Variables As Terms to Formula

Low-Level Fitting Function for MMRM

covariance_types

Covariance Types

h_dataset_sort_all

Sort a Data Frame by All Its Columns in Ascending Order

h_confirm_large_levels

Ask for Confirmation on Large Visit Levels

h_anova_single_mmrm_model

Calculate the Significance of Each Term in an mmrm Fit.

h_default_value

Default Value on NULL Return default value when first argument is NULL.

h_assert_lrt_suitability

Ensure LRT Is Appropriate for list of mmrm Fits

Calculation of Between-Within Degrees of Freedom

Retrieve Associated Full Covariance Structure Type Name

h_construct_model_frame_inputs

Construction of Model Frame Formula and Data Inputs

Add Formula Terms with Character

h_contr_sum_type3_contrasts

Construct Preliminary Contrast Matrices for Type III Tests Assuming Sum Contrasts

Extract Right-Hand-Side (rhs) from Formula

Calculation of Between-Within Degrees of Freedom for One-Dimensional Contrast

Calculation of Satterthwaite Degrees of Freedom for Multi-Dimensional Contrast

Calculation of Residual Degrees of Freedom for Multi-Dimensional Contrast

Flatten Expressions for Non-standard Evaluation

h_drop_covariance_terms

Drop Formula Terms used for Covariance Structure Definition

Drop Levels from Dataset

Calculation of Between-Within Degrees of Freedom for Multi-Dimensional Contrast

fit_single_optimizer

Fitting an MMRM with Single Optimizer

h_get_na_action

Obtain na.action as Function

h_get_optimizers

Obtain Optimizer according to Optimizer String Value

Calculation of Satterthwaite Degrees of Freedom for One-Dimensional Contrast

Computation of a Gradient Given Jacobian and Contrast Vector

Build TMB Fit Result List

Obtain List of Jacobian Matrix Entries for Covariance Matrix

h_get_empirical

Obtain Empirical/Jackknife/Bias-Reduced Covariance

Calculation of Residual Degrees of Freedom for One-Dimensional Contrast

h_check_cov_struct_nesting

Ensure Two Models' Covariance Structures Are Nested

h_mmrm_tmb_data

Data for TMB Fit

h_check_columns_nested

Predicate Indicating Whether Two Datasets Contain the Same Observations

Calculation of Kenward-Roger Degrees of Freedom for One-Dimensional Contrast

h_generate_new_name

Generate a Name Not Already In an Environment nor Its Parents

h_get_cov_default

Obtain Default Covariance Method

h_assert_nested_models

Ensure Two Models Are Nested

h_check_covar_nesting

Ensure Two Models' Covariates Are Nested

Calculation of Kenward-Roger Degrees of Freedom for Multi-Dimensional Contrast

h_first_term_containing_categ

Identify the First Term in a Model to Contain a Categorical Variable

h_df_md_from_1d

Creating F-Statistic Results from One-Dimensional Contrast

h_mmrm_tmb_extract_cov

Extract covariance matrix from TMB report and input data

h_mmrm_tmb_parameters

Start Parameters for TMB Fit

h_newdata_add_pred

Add Prediction Results to New Data

h_df_1d_sat_empirical

Helper for Calculation of Satterthwaite with Empirical Covariance Matrix

Check if a Factor Should Drop Levels

Obtain Levels Prior and Posterior

h_mmrm_tmb_assert_start

Asserting Sane Start Values for TMB Fit

h_mmrm_tmb_check_conv

Checking the TMB Optimization Result

Obtain Kenward-Roger Adjustment Components

h_get_theta_from_cov

Obtain Theta from Covariance Matrix

Test if the First Vector is Subset of the Second Vector

h_fits_common_data

Combine the Datasets from mmrm Fits

h_optimizer_fun

Obtain Optimizer Function with Character

h_print_aic_list

Printing AIC and other Model Fit Criteria

h_get_minimal_fit_data

Obtain the Minimal Dataset Needed for an mmrm Fit

h_partial_fun_args

Create Partial Functions

h_get_sim_per_subj

Get simulated values by patient.

Quadratic Form Calculations

h_extract_covariance_terms

Extract Formula Terms used for Covariance Structure Definition

Obtain the Adjusted Covariance Matrix

h_valid_formula

Validate mmrm Formula

Register S3 Method Register S3 method to a generic.

h_residuals_pearson

Calculate Pearson Residuals

h_residuals_normalized

Calculate normalized residuals

h_mmrm_tmb_formula_parts

Processing the Formula for TMB Fit

h_warn_na_action

Warn on na.action

position_symbol

Search For the Position of a Symbol

h_within_or_between

Determine Within or Between for each Design Matrix Column

h_residuals_response

Calculate response residuals.

h_tmb_warn_non_deterministic

Warn if TMB is Configured to Use Non-Deterministic Hash for Tape Optimizer

Creating F- or Chi-squared-statistic Test Results For Multi-Dimensional Contrast

h_reconcile_cov_struct

Reconcile Possible Covariance Structure Inputs

Trace of a Matrix

h_tmb_version_sufficient

Predicate if the TMB Version Used to Compile the Package is Sufficient

Printing MMRM Function Call

h_check_fits_all_data_same

Predicate Indicating Whether mmrm Fits' Datasets Contain the Same Observations

format.cov_struct

Format Covariance Structure Object

print.cov_struct

Print a Covariance Structure Object

Coefficients Table for MMRM Fit

Printing MMRM Covariance Type

h_split_control

Split Control List

h_summarize_all_fits

Summarizing List of Fits

h_type2_contrast

Obtain Type 2 Contrast for One Specified Effect

Control Parameters for Fitting an MMRM

mmrm_tmb_methods

Methods for mmrm_tmb Objects

Test Whether a Symbol is an Infix Operator

h_type3_contrasts

Obtain Type 3 Contrast for All Effects

parsnip_add_mmrm

Register mmrm For Use With tidymodels

refit_multiple_optimizers

Refitting MMRM with Multiple Optimizers

Assign Minimum Degrees of Freedom Given Involved Coefficients

Objects exported from other packages

Calculating Denominator Degrees of Freedom for the Multi-Dimensional Case

h_get_prediction_variance

Get Prediction Variance

Coerce a Data Frame to a tibble

Methods for mmrm Objects

Tidying Methods for mmrm Objects

Obtain the Adjusted Kenward-Roger degrees of freedom

h_get_prediction

Analysis of Variance for mmrm Fits

validate_cov_struct

Validate Covariance Structure Data

register_on_load

Helper Function for Registering Functionality With Suggests Packages

h_record_all_output

Capture all Output

Refit an mmrm Model Using a New Dataset

h_tbl_confint_terms

Extract tibble with Confidence Intervals and Term Names

Produce A Covariance Identifier Passing to TMB

Standard Starting Value

Creating T-Statistic Test Results For One-Dimensional Contrast

Coerce into a Covariance Structure Definition

Retrieve Associated Abbreviated Covariance Structure Type Name

Define a Covariance Structure

Component Access for mmrm_tmb Objects

Calculation of Degrees of Freedom for One-Dimensional Contrast

Covariance Type Database

Drop Items from an Indexible

Example Data on FEV1

cached_mmrm_results

Cache Data for mmrm Model Comparison

Complete character Vector Names From Values

Example Data on BCVA

Conduct type II/III hypothesis testing on the MMRM fit results.

check_package_version

Check Suggested Dependency Against Version Requirements

Register mmrm For Use With car::Anova