compute_InfoContent

Title Formula-based calculation of information content

Tools for power and sample size
calculation as well as design diagnostics for
longitudinal mixed model settings, with a focus on stepped wedge designs.
All calculations are oracle estimates i.e. assume random effect variances
to be known (or guessed) in advance.
The method is introduced in Hussey and Hughes (2007) <doi:10.1016/j.cct.2006.05.007>,
extensions are discussed in Li et al. (2020) <doi:10.1177/0962280220932962>.

Philipp Mildenberger

SteppedPower

Power Calculation for Stepped Wedge Designs

Federico Marini

compute_InfoContent function

<dl><dt>CovMat</dt>
<dd>#' @param CovMat numeric, a positive-semidefinite matrix with
(#Clusters \(\cdot\) timepoints) rows and columns.</dd>
<dt>W</dt>
<dd>numeric, the inverse of a covariance matrix. If CovMat is specified,
input for W is ignored</dd>
<dt>dsn</dt>
<dd>a matrix with (#Clusters \(\cdot\) #timepoints) rows and p
columns, where p are the degrees of freedom of fixed effects in a gls model.
This usually contains the intervention effect and some specification of the
time effect.</dd>
<dt>sumCl</dt>
<dd>number of clusters</dd>
<dt>tp</dt>
<dd>number of time points</dd></dl>

Arguments

Title  Formula-based calculation of information content — compute_InfoContent

<dl>

<dt>CovMat</dt>
<dd>#' @param CovMat numeric, a positive-semidefinite matrix with
(#Clusters \(\cdot\) timepoints) rows and columns.</dd>


<dt>W</dt>
<dd>numeric, the inverse of a covariance matrix. If CovMat is specified,
input for W is ignored</dd>


<dt>dsn</dt>
<dd>a matrix with (#Clusters \(\cdot\) #timepoints) rows and p
columns, where p are the degrees of freedom of fixed effects in a gls model.
This usually contains the intervention effect and some specification of the
time effect.</dd>


<dt>sumCl</dt>
<dd>number of clusters</dd>


<dt>tp</dt>
<dd>number of time points</dd>

</dl>

compute_InfoContent: Title Formula-based calculation of information content

Description

Usage

Value

Arguments