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mmrm (version 0.3.12)

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

3,712

Version

0.3.12

License

Apache License 2.0

Maintainer

Daniel Sabanes Bove

Last Published

June 26th, 2024

Functions in mmrm (0.3.12)

emit_tidymodels_register_msg

Format a Message to Emit When Tidymodels is Loaded

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

h_default_value

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

h_extract_covariance_terms

Extract Formula Terms used for Covariance Structure Definition

h_drop_covariance_terms

Drop Formula Terms used for Covariance Structure Definition

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

Low-Level Fitting Function for MMRM

fit_single_optimizer

Fitting an MMRM with Single Optimizer

Assign Minimum Degrees of Freedom Given Involved Coefficients

covariance_types

Covariance Types

Calculation of Degrees of Freedom for One-Dimensional Contrast

Calculation of Residual Degrees of Freedom for One-Dimensional Contrast

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

Coerce a Data Frame to a tibble

h_confirm_large_levels

Ask for Confirmation on Large Visit Levels

Calculation of Satterthwaite Degrees of Freedom for One-Dimensional Contrast

h_get_empirical

Obtain Empirical/Jackknife/Bias-Reduced Covariance

Obtain List of Jacobian Matrix Entries for Covariance Matrix

h_factor_ref_data

Convert Character to Factor Following Reference MMRM Fit.

h_get_optimizers

Obtain Optimizer according to Optimizer String Value

Format Symbol Objects

Retrieve Associated Full Covariance Structure Type Name

Convert Character to Factor Following Reference

Calculation of Between-Within Degrees of Freedom

h_partial_fun_args

Create Partial Functions

Obtain Contrast for Specified Effect

h_print_aic_list

Printing AIC and other Model Fit Criteria

Obtain the Adjusted Kenward-Roger degrees of freedom

Obtain Kenward-Roger Adjustment Components

format.cov_struct

Format Covariance Structure Object

Calculation of Degrees of Freedom for Multi-Dimensional Contrast

h_get_cov_default

Obtain Default Covariance Method

Extract Right-Hand-Side (rhs) from Formula

Trace of a Matrix

Flatten Expressions for Non-standard Evaluation

Calculating Denominator Degrees of Freedom for the Multi-Dimensional Case

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

h_valid_formula

Validate mmrm Formula

h_mmrm_tmb_check_conv

Checking the TMB Optimization Result

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

Calculation of Residual Degrees of Freedom for Multi-Dimensional Contrast

h_mmrm_tmb_data

Data for TMB Fit

Calculation of Satterthwaite Degrees of Freedom for Multi-Dimensional Contrast

Control Parameters for Fitting an MMRM

Quadratic Form Calculations

h_get_prediction

Printing MMRM Function Call

h_newdata_add_pred

Add Prediction Results to New Data

h_summarize_all_fits

Summarizing List of Fits

Methods for mmrm Objects

h_mmrm_tmb_assert_start

Asserting Sane Start Values for TMB Fit

Printing MMRM Covariance Type

h_optimizer_fun

Obtain Optimizer Function with Character

h_record_all_output

Capture all Output

print.cov_struct

Print a Covariance Structure Object

h_reconcile_cov_struct

Reconcile Possible Covariance Structure Inputs

Register S3 Method Register S3 method to a generic.

h_get_prediction_variance

Get Prediction Variance

Creating T-Statistic Test Results For One-Dimensional Contrast

h_get_sim_per_subj

Get simulated values by patient.

h_mmrm_tmb_extract_cov

Extract covariance matrix from TMB report and input data

Build TMB Fit Result List

Tidying Methods for mmrm Objects

refit_multiple_optimizers

Refitting MMRM with Multiple Optimizers

h_get_theta_from_cov

Obtain Theta from Covariance Matrix

h_residuals_normalized

Calculate normalized residuals

h_tbl_confint_terms

Extract tibble with Confidence Intervals and Term Names

parsnip_add_mmrm

Register mmrm For Use With tidymodels

h_warn_na_action

Warn on na.action

h_mmrm_tmb_formula_parts

Processing the Formula for TMB Fit

Obtain the Adjusted Covariance Matrix

mmrm_tmb_methods

Methods for mmrm_tmb Objects

Computation of a Gradient Given Jacobian and Contrast Vector

h_residuals_pearson

Calculate Pearson Residuals

h_split_control

Split Control List

h_within_or_between

Determine Within or Between for each Design Matrix Column

Creating F-Statistic Test Results For Multi-Dimensional Contrast

h_residuals_response

Calculate response residuals.

validate_cov_struct

Validate Covariance Structure Data

Objects exported from other packages

Test Whether a Symbol is an Infix Operator

h_mmrm_tmb_parameters

Start Parameters for TMB Fit

Standard Starting Value

position_symbol

Search For the Position of a Symbol

register_on_load

Helper Function for Registering Functionality With Suggests Packages

Produce A Covariance Identifier Passing to TMB

check_package_version

Check Suggested Dependency Against Version Requirements

Component Access for mmrm_tmb Objects

Coerce into a Covariance Structure Definition

Define a Covariance Structure

Covariance Type Database

Drop Items from an Indexible

Retrieve Associated Abbreviated Covariance Structure Type Name

Example Data on BCVA

cached_mmrm_results

Cache Data for mmrm Model Comparison

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

Register mmrm For Use With car::Anova

Example Data on FEV1

Complete character Vector Names From Values

Empirical Starting Value

emmeans_support

Support for emmeans

h_add_covariance_terms

Add Individual Covariance Variables As Terms to Formula

Coefficients Table for MMRM Fit

Add Formula Terms with Character