loglikelihood_binary

log likelihood of Bernoulli function

Design and analyze three-arm non-inferiority or superiority trials
which follow a gold-standard design, i.e. trials with an experimental treatment,
an active, and a placebo control. Method for the following distributions are implemented:
Poisson (Mielke and Munk (2009) <arXiv:0912.4169>), negative binomial (Muetze et al. (2016) <doi:10.1002/sim.6738>),
normal (Pigeot et al. (2003) <doi:10.1002/sim.1450>; Hasler et al. (2009) <doi:10.1002/sim.3052>),
binary (Friede and Kieser (2007) <doi:10.1002/sim.2543>), nonparametric (Muetze et al. (2017) <doi:10.1002/sim.7176>),
exponential (Mielke and Munk (2009) <arXiv:0912.4169>).

Tobias Muetze

ThreeArmedTrials

Design and Analysis of Clinical Non-Inferiority or Superiority
Trials with Active and Placebo Control

Tobias Mütze

Tim Friede

loglikelihood_binary function

<dl><dt>p</dt>
<dd>numeric vector of probabilities with length 3</dd>
<dt>xExp</dt>
<dd>numeric vector of probabilities with length 3</dd>
<dt>xRef</dt>
<dd>numeric vector of probabilities with length 3</dd>
<dt>xPla</dt>
<dd>numeric vector of probabilities with length 3</dd></dl>

Arguments

loglikelihood_binary — loglikelihood_binary

<dl>

<dt>p</dt>
<dd>numeric vector of probabilities with length 3</dd>


<dt>xExp</dt>
<dd>numeric vector of probabilities with length 3</dd>


<dt>xRef</dt>
<dd>numeric vector of probabilities with length 3</dd>


<dt>xPla</dt>
<dd>numeric vector of probabilities with length 3</dd>

</dl>

loglikelihood_binary: loglikelihood_binary

Description

Usage

Arguments