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mmrm (version 0.3.15)

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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Version

Install

install.packages('mmrm')

Monthly Downloads

6,381

Version

0.3.15

License

Apache License 2.0

Maintainer

Daniel Sabanes Bove

Last Published

June 10th, 2025

Functions in mmrm (0.3.15)

Add Formula Terms with Character

fit_single_optimizer

Fitting an MMRM with Single Optimizer

Low-Level Fitting Function for MMRM

Flatten Expressions for Non-standard Evaluation

h_add_covariance_terms

Add Individual Covariance Variables As Terms to Formula

format.cov_struct

Format Covariance Structure Object

Example Data on FEV1

Complete character Vector Names From Values

Extract Right-Hand-Side (rhs) from Formula

Format Symbol Objects

h_confirm_large_levels

Ask for Confirmation on Large Visit Levels

Coefficients Table for MMRM Fit

h_default_value

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

Calculation of Satterthwaite Degrees of Freedom for One-Dimensional Contrast

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

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

Calculation of Residual Degrees of Freedom for One-Dimensional Contrast

h_df_1d_sat_empirical

Helper for Calculation of Satterthwaite with Empirical Covariance Matrix

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

Calculation of Between-Within Degrees of Freedom

h_df_md_from_1d

Creating F-Statistic Results from One-Dimensional Contrast

h_construct_model_frame_inputs

Construction of Model Frame Formula and Data Inputs

Drop Levels from Dataset

Assign Minimum Degrees of Freedom Given Involved Coefficients

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

Calculation of Satterthwaite Degrees of Freedom for Multi-Dimensional Contrast

h_drop_covariance_terms

Drop Formula Terms used for Covariance Structure Definition

Coerce a Data Frame to a tibble

Calculation of Residual Degrees of Freedom for Multi-Dimensional Contrast

Check if a Factor Should Drop Levels

h_first_contain_categorical

Check if the Effect is the First Categorical Effect

h_extract_covariance_terms

Extract Formula Terms used for Covariance Structure Definition

Obtain Contrast for Specified Effect

h_get_sim_per_subj

Get simulated values by patient.

h_get_cov_default

Obtain Default Covariance Method

h_get_theta_from_cov

Obtain Theta from Covariance Matrix

Obtain Kenward-Roger Adjustment Components

h_get_optimizers

Obtain Optimizer according to Optimizer String Value

Test if the First Vector is Subset of the Second Vector

h_get_prediction_variance

Get Prediction Variance

Printing MMRM Covariance Type

h_print_aic_list

Printing AIC and other Model Fit Criteria

h_optimizer_fun

Obtain Optimizer Function with Character

Quadratic Form Calculations

h_mmrm_tmb_parameters

Start Parameters for TMB Fit

Calculating Denominator Degrees of Freedom for the Multi-Dimensional Case

h_mmrm_tmb_check_conv

Checking the TMB Optimization Result

h_get_prediction

Obtain List of Jacobian Matrix Entries for Covariance Matrix

Computation of a Gradient Given Jacobian and Contrast Vector

h_get_na_action

Obtain na.action as Function

h_mmrm_tmb_extract_cov

Extract covariance matrix from TMB report and input data

h_get_empirical

Obtain Empirical/Jackknife/Bias-Reduced Covariance

Obtain the Adjusted Kenward-Roger degrees of freedom

Printing MMRM Function Call

h_partial_fun_args

Create Partial Functions

h_mmrm_tmb_formula_parts

Processing the Formula for TMB Fit

h_mmrm_tmb_data

Data for TMB Fit

h_mmrm_tmb_assert_start

Asserting Sane Start Values for TMB Fit

h_newdata_add_pred

Add Prediction Results to New Data

Register S3 Method Register S3 method to a generic.

Obtain Levels Prior and Posterior

h_residuals_normalized

Calculate normalized residuals

h_split_control

Split Control List

h_record_all_output

Capture all Output

h_residuals_response

Calculate response residuals.

Creating T-Statistic Test Results For One-Dimensional Contrast

h_tbl_confint_terms

Extract tibble with Confidence Intervals and Term Names

Build TMB Fit Result List

h_summarize_all_fits

Summarizing List of Fits

h_residuals_pearson

Calculate Pearson Residuals

h_within_or_between

Determine Within or Between for each Design Matrix Column

h_tmb_version_sufficient

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

h_reconcile_cov_struct

Reconcile Possible Covariance Structure Inputs

Trace of a Matrix

Test Whether a Symbol is an Infix Operator

Obtain the Adjusted Covariance Matrix

h_tmb_warn_non_deterministic

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

h_valid_formula

Validate mmrm Formula

h_warn_na_action

Warn on na.action

Creating F-Statistic Test Results For Multi-Dimensional Contrast

Control Parameters for Fitting an MMRM

print.cov_struct

Print a Covariance Structure Object

position_symbol

Search For the Position of a Symbol

Tidying Methods for mmrm Objects

refit_multiple_optimizers

Refitting MMRM with Multiple Optimizers

parsnip_add_mmrm

Register mmrm For Use With tidymodels

mmrm_tmb_methods

Methods for mmrm_tmb Objects

Produce A Covariance Identifier Passing to TMB

Methods for mmrm Objects

Objects exported from other packages

Standard Starting Value

validate_cov_struct

Validate Covariance Structure Data

register_on_load

Helper Function for Registering Functionality With Suggests Packages

Retrieve Associated Abbreviated Covariance Structure Type Name

Coerce into a Covariance Structure Definition

Define a Covariance Structure

Component Access for mmrm_tmb Objects

Calculation of Degrees of Freedom for One-Dimensional Contrast

Calculation of Degrees of Freedom for Multi-Dimensional Contrast

covariance_types

Covariance Types

Empirical Starting Value

emmeans_support

Support for emmeans

Covariance Type Database

Example Data on BCVA

Drop Items from an Indexible

cached_mmrm_results

Cache Data for mmrm Model Comparison

Retrieve Associated Full Covariance Structure Type Name

check_package_version

Check Suggested Dependency Against Version Requirements

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

emit_tidymodels_register_msg

Format a Message to Emit When Tidymodels is Loaded

Register mmrm For Use With car::Anova