Computes p-values for a given set of random variables under a t-distribution with fixed degrees of freedom.

internal

Sample size estimation for bio-equivalence trials is supported through a simulation-based approach
that extends the Two One-Sided Tests (TOST) procedure. The methodology provides flexibility in
hypothesis testing, accommodates multiple treatment comparisons, and accounts for correlated endpoints.
Users can model complex trial scenarios, including parallel and crossover designs, intra-subject variability,
and different equivalence margins. Monte Carlo simulations enable accurate estimation of power and type I error
rates, ensuring well-calibrated study designs. The statistical framework builds on established methods for
equivalence testing and multiple hypothesis testing in bio-equivalence studies, as described in Schuirmann (1987)
<doi:10.1007/BF01068419>, Mielke et al. (2018) <doi:10.1080/19466315.2017.1371071>, Shieh (2022)
<doi:10.1371/journal.pone.0269128>, and Sozu et al. (2015) <doi:10.1007/978-3-319-22005-5>.
Comprehensive documentation and vignettes guide users through implementation and interpretation of results.

Thomas Debray

SimTOST

Sample Size Estimation for Bio-Equivalence Trials Through
Simulation

Johanna Munoz

Dewi Amaliah

Wei Wei

Marian Mitroiu

Scott McDonald

Biogen Inc 

ptv function

<dl><dt>x</dt>
<dd>A numeric matrix (or vector) representing the random variables.</dd>
<dt>df</dt>
<dd>A double specifying the degrees of freedom.</dd>
<dt>lower</dt>
<dd>A logical value indicating whether to compute the lower-tail probability (<code>P(T &lt;= x)</code>). If <code>FALSE</code>, the function returns the upper-tail probability (<code>P(T &gt; x)</code>).</dd></dl>

Arguments

Compute p-values for a t-distribution with Fixed Degrees of Freedom — ptv

<dl>

<dt>x</dt>
<dd>A numeric matrix (or vector) representing the random variables.</dd>


<dt>df</dt>
<dd>A double specifying the degrees of freedom.</dd>


<dt>lower</dt>
<dd>A logical value indicating whether to compute the lower-tail probability (<code>P(T &lt;= x)</code>). If <code>FALSE</code>, the function returns the upper-tail probability (<code>P(T &gt; x)</code>).</dd>

</dl>

ptv: Compute p-values for a t-distribution with Fixed Degrees of Freedom

Description

Usage

Value

Arguments