conditional_Sigma

See e.g. Chapter 8.1.2 in <a href="https://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf">The Matrix Cookbook</a>.

Methods to calculate optimal design parameters
for one- and two-stage three-arm group-sequential gold-standard
non-inferiority trial designs
with or without binding or nonbinding futility boundaries,
as described in Meis et al. (2023) <doi:10.1002/sim.9630>.

Jan Meis

OptimalGoldstandardDesigns

Design Parameter Optimization for Gold-Standard Non-Inferiority
Trials

conditional_Sigma function

<dl><dt>x_a</dt>
<dd>(Observed) first part of normally distributed vector.</dd>
<dt>mu_a</dt>
<dd>Mean of second part of normally distributed vector.</dd>
<dt>mu_b</dt>
<dd>Mean of first part of normally distributed vector.</dd>
<dt>Sigma</dt>
<dd>covariance matrix of test statistic vector c(Z_TP1, Z_TP2, Z_TC1, Z_TC2).</dd></dl>

Arguments

See e.g. Chapter 8.1.2 in <a href='https://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf'>The Matrix Cookbook</a>.

Calculate the conditional mean of a multivariate normal distribution — conditional_Sigma

<dl>

<dt>x_a</dt>
<dd>(Observed) first part of normally distributed vector.</dd>


<dt>mu_a</dt>
<dd>Mean of second part of normally distributed vector.</dd>


<dt>mu_b</dt>
<dd>Mean of first part of normally distributed vector.</dd>


<dt>Sigma</dt>
<dd>covariance matrix of test statistic vector c(Z_TP1, Z_TP2, Z_TC1, Z_TC2).</dd>

</dl>

conditional_Sigma: Calculate the conditional mean of a multivariate normal distribution

Description

Usage

Value

Arguments

References