get_example_design

The design was optimized to minimize the expected sample size
under the alternative hypothesis for a one-armed trial.
The boundaries are chosen to control the type I error at 0.025
for a normally distributed test statistic (i.e. known variance).
For an alternative hypothesis of mu=0.4, the overall power is 80%.

Methods to evaluate the performance characteristics of
various point and interval estimators for optimal adaptive two-stage designs as described
in Meis et al. (2024) <doi:10.1002/sim.10020>.
Specifically, this package is written to work with trial designs created by the 'adoptr' package
(Kunzmann et al. (2021) <doi:10.18637/jss.v098.i09>; Pilz et al. (2021) <doi:10.1002/sim.8953>)).
Apart from the a priori evaluation of performance characteristics, this package also allows for the
evaluation of the implemented estimators on real datasets, and it implements methods
to calculate p-values.

Jan Meis

adestr

Estimation in Optimal Adaptive Two-Stage Designs

Martin Maechler

get_example_design function

<dl><dt>two_armed</dt>
<dd>(logical) determins whether the design is for one- or
two-armed trials.</dd>
<dt>label</dt>
<dd>(optional) label to be assigned to the design.</dd></dl>

Arguments

Generate an exemplary adaptive design — get_example_design

<dl>

<dt>two_armed</dt>
<dd>(logical) determins whether the design is for one- or
two-armed trials.</dd>


<dt>label</dt>
<dd>(optional) label to be assigned to the design.</dd>

</dl>

get_example_design: Generate an exemplary adaptive design

Description

Usage

Value

Arguments

Examples