create_conditions

This function creates a character vector of treatment conditions
using the conditions column in the provided data, and if <code>control_augment</code> is greater
than 0, it also labels the control condition. Throws an error of <code>control_condition</code> is not
present.

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

create_conditions function

<dl><dt>control_condition</dt>
<dd>Value of the control condition. Only necessary when <code>control_augment</code> is greater than 0. Internally this value
is coerced to a string, so it should be passed as a string, or a type that can easily be converted to a string.</dd>
<dt>data</dt>
<dd>A data.frame, data.table, or tibble containing input data from the trial. This should be the results
of a traditional Randomized Controlled Trial (RCT). Any data.frames will be converted to tibbles internally.</dd>
<dt>condition_col</dt>
<dd>Column in <code>data</code>; original treatment condition for each observation.</dd>
<dt>control_augment</dt>
<dd>A numeric value ranging from 0 to 1; proportion of each wave guaranteed to receive the "Control" treatment.
Default is 0. It is not recommended to use this in conjunction with <code>random_assign_prop</code>.</dd></dl>

Arguments

Creating proper conditions vector — create_conditions

<dl>

<dt>control_condition</dt>
<dd>Value of the control condition. Only necessary when <code>control_augment</code> is greater than 0. Internally this value
is coerced to a string, so it should be passed as a string, or a type that can easily be converted to a string.</dd>


<dt>data</dt>
<dd>A data.frame, data.table, or tibble containing input data from the trial. This should be the results
of a traditional Randomized Controlled Trial (RCT). Any data.frames will be converted to tibbles internally.</dd>


<dt>condition_col</dt>
<dd>Column in <code>data</code>; original treatment condition for each observation.</dd>


<dt>control_augment</dt>
<dd>A numeric value ranging from 0 to 1; proportion of each wave guaranteed to receive the "Control" treatment.
Default is 0. It is not recommended to use this in conjunction with <code>random_assign_prop</code>.</dd>

</dl>

create_conditions: Creating proper conditions vector

Description

Usage

Value

Arguments