check_level

Checking if the <code>level</code> argument in the S3 generic methods
is valid for a confidence interval.

internal

Simulates the results of completed randomized controlled
trials, as if they had been conducted as adaptive Multi-Arm Bandit
(MAB) trials instead. Augmented inverse probability weighted
estimation (AIPW), outlined by Hadad et al. (2021)
<doi:10.1073/pnas.2014602118>, is used to robustly estimate the
probability of success for each treatment arm under the adaptive
design. Provides customization options to simulate perfect/imperfect
information, stationary/non-stationary bandits, blocked treatment
assignments, along with control augmentation, and other hybrid
strategies for assigning treatment arms. The methods used in
simulation were inspired by Offer-Westort et al. (2021)
<doi:10.1111/ajps.12597>.

Noah Ochital

whatifbandit

Analyzing Randomized Experiments as Multi-Arm Bandits

Ryan T. Moore

check_level function

<dl><dt>level</dt>
<dd>Numeric value of length 1; indicates confidence interval Width (i.e 0.90, 0.95, 0.99).
Defaults to 0.95.</dd></dl>

Arguments

Check Level — check_level

<dl>

<dt>level</dt>
<dd>Numeric value of length 1; indicates confidence interval Width (i.e 0.90, 0.95, 0.99).
Defaults to 0.95.</dd>

</dl>

check_level: Check Level

Description

Usage

Value

Arguments