Mixed Models for Repeated Measures
Conduct type II/III hypothesis testing on the MMRM fit results.
Coerce into a Covariance Structure Definition
Register mmrm For Use With car::Anova
Check Suggested Dependency Against Version Requirements
Component Access for mmrm_tmb Objects
Define a Covariance Structure
Retrieve Associated Abbreviated Covariance Structure Type Name
Retrieve Associated Full Covariance Structure Type Name
Covariance Type Database
Covariance Types
Calculation of Degrees of Freedom for One-Dimensional Contrast
Calculation of Degrees of Freedom for Multi-Dimensional Contrast
Drop Items from an Indexible
Format a Message to Emit When Tidymodels is Loaded
Support for emmeans
Empirical Starting Value
Complete character Vector Names From Values
Low-Level Fitting Function for MMRM
Fitting an MMRM with Single Optimizer
Flatten Expressions for Non-standard Evaluation
Format Symbol Objects
Format Covariance Structure Object
Extract Right-Hand-Side (rhs) from Formula
Add Individual Covariance Variables As Terms to Formula
Add Formula Terms with Character
Coefficients Table for MMRM Fit
Ask for Confirmation on Large Visit Levels
Construction of Model Frame Formula and Data Inputs
Default Value on NULL Return default value when first argument is NULL...
Calculation of Between-Within Degrees of Freedom for One-Dimensional C...
Calculation of Kenward-Roger Degrees of Freedom for One-Dimensional Co...
Calculation of Residual Degrees of Freedom for One-Dimensional Contras...
Calculation of Satterthwaite Degrees of Freedom for One-Dimensional Co...
Calculation of Between-Within Degrees of Freedom
Calculation of Between-Within Degrees of Freedom for Multi-Dimensional...
Creating F-Statistic Results from One-Dimensional Contrast
Calculation of Kenward-Roger Degrees of Freedom for Multi-Dimensional ...
Calculation of Residual Degrees of Freedom for Multi-Dimensional Contr...
Calculation of Satterthwaite Degrees of Freedom for Multi-Dimensional ...
Assign Minimum Degrees of Freedom Given Involved Coefficients
Coerce a Data Frame to a tibble
Drop Formula Terms used for Covariance Structure Definition
Drop Levels from Dataset
Check if a Factor Should Drop Levels
Extract Formula Terms used for Covariance Structure Definition
Check if the Effect is the First Categorical Effect
Obtain Contrast for Specified Effect
Obtain Default Covariance Method
Obtain Empirical/Jackknife/Bias-Reduced Covariance
Test if the First Vector is Subset of the Second Vector
Obtain Kenward-Roger Adjustment Components
Obtain na.action as Function
Obtain Optimizer according to Optimizer String Value
Get Prediction Variance
Get Prediction
Get simulated values by patient.
Obtain Theta from Covariance Matrix
Computation of a Gradient Given Jacobian and Contrast Vector
Obtain List of Jacobian Matrix Entries for Covariance Matrix
Obtain the Adjusted Kenward-Roger degrees of freedom
Calculating Denominator Degrees of Freedom for the Multi-Dimensional C...
Asserting Sane Start Values for TMB Fit
Checking the TMB Optimization Result
Data for TMB Fit
Extract covariance matrix from TMB report and input data
Build TMB Fit Result List
Processing the Formula for TMB Fit
Start Parameters for TMB Fit
Add Prediction Results to New Data
Obtain Levels Prior and Posterior
Obtain Optimizer Function with Character
Create Partial Functions
Printing AIC and other Model Fit Criteria
Printing MMRM Function Call
Printing MMRM Covariance Type
Quadratic Form Calculations
Reconcile Possible Covariance Structure Inputs
Capture all Output
Register S3 Method Register S3 method to a generic.
Calculate normalized residuals
Calculate Pearson Residuals
Calculate response residuals.
Split Control List
Summarizing List of Fits
Extract tibble with Confidence Intervals and Term Names
Creating T-Statistic Test Results For One-Dimensional Contrast
Creating F-Statistic Test Results For Multi-Dimensional Contrast
Warn if TMB is Configured to Use Non-Deterministic Hash for Tape Optim...
Trace of a Matrix
Validate mmrm Formula
Obtain the Adjusted Covariance Matrix
Warn on na.action
Determine Within or Between for each Design Matrix Column
Test Whether a Symbol is an Infix Operator
Control Parameters for Fitting an MMRM
Methods for mmrm Objects
Tidying Methods for mmrm Objects
Methods for mmrm_tmb Objects
mmrm Package
Fit an MMRM
Register mmrm For Use With tidymodels
Search For the Position of a Symbol
Print a Covariance Structure Object
Objects exported from other packages
Refitting MMRM with Multiple Optimizers
Helper Function for Registering Functionality With Suggests Packages
Standard Starting Value
Produce A Covariance Identifier Passing to TMB
Validate Covariance Structure Data
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) <doi:10.1002/(SICI)1097-0258(19971030)16:20%3C2349::AID-SIM667%3E3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) <doi:10.1177/009286150804200402> 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'.