h_test_1d

Creates a list of results for one-dimensional contrasts using
a t-test statistic and the given degrees of freedom.

internal

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'.

Daniel Sabanes Bove

mmrm

Mixed Models for Repeated Measures

Liming Li

Julia Dedic

Doug Kelkhoff

Kevin Kunzmann

Brian Matthew Lang

Christian Stock

Ya Wang

Craig Gower-Page

Dan James

Jonathan Sidi

Daniel Leibovitz

Daniel D. Sjoberg

Nikolas Ivan Krieger

Lukas A. Widmer

Boehringer Ingelheim Ltd. 

Gilead Sciences, Inc. 

F. Hoffmann-La Roche AG 

Merck Sharp & Dohme, Inc. 

AstraZeneca plc 

inferential.biostatistics GmbH 

h_test_1d function

<dl><dt>object</dt>
<dd>(<code>mmrm</code>) the MMRM fit.</dd>
<dt>contrast</dt>
<dd>(<code>numeric</code>) contrast vector. Note that this should not include
elements for singular coefficient estimates, i.e. only refer to the
actually estimated coefficients.</dd>
<dt>df</dt>
<dd>(<code>number</code>) degrees of freedom for the one-dimensional contrast.</dd></dl>

Arguments

Creating T-Statistic Test Results For One-Dimensional Contrast — h_test_1d

<dl>

<dt>object</dt>
<dd>(<code>mmrm</code>) the MMRM fit.</dd>


<dt>contrast</dt>
<dd>(<code>numeric</code>) contrast vector. Note that this should not include
elements for singular coefficient estimates, i.e. only refer to the
actually estimated coefficients.</dd>


<dt>df</dt>
<dd>(<code>number</code>) degrees of freedom for the one-dimensional contrast.</dd>

</dl>

Creating T-Statistic Test Results For One-Dimensional Contrast

h_test_1d: Creating T-Statistic Test Results For One-Dimensional Contrast

Description

Usage

Value

Arguments