control_clusters

A dataset containing the covariates, aggregated outcome,
aggregated treatment received, number of units, and the
cluster-level IV of 100 matched control clusters. There is
a one-to-one correspondence between this 100 matched
control clusters and 100 matched encouraged clusters: the kth
control cluster is matched to the kth encouraged cluster in
<code><a rd-options="" href="/link/encouraged_clusters?package=ivdesign&version=0.1.0" data-mini-rdoc="ivdesign::encouraged_clusters">encouraged_clusters</a></code>.

datasets

An implementation of randomization-based hypothesis
testing for three different estimands in a cluster-randomized
encouragement experiment. The three estimands include (1) testing
a cluster-level constant proportional treatment effect (Fisher's
sharp null hypothesis), (2) pooled effect ratio, and (3) average
cluster effect ratio. To test the third estimand, user needs to install
'Gurobi' (>= 9.0.1) optimizer via its R API. Please refer to
<https://www.gurobi.com/documentation/9.0/refman/ins_the_r_package.html>.

Bo Zhang

ivdesign

Hypothesis Testing in Cluster-Randomized Encouragement Designs

control_clusters function

A data frame with 100 rows and 14 columns:<dl class="dl-horizontal">
 <dt>V1</dt><dd>1st simulated covariate</dd>
 <dt>V2</dt><dd>2nd simulated covariate</dd>
 <dt>V3</dt><dd>3rd simulated covariate</dd>
 <dt>V4</dt><dd>4th simulated covariate</dd>
 <dt>V5</dt><dd>5th simulated covariate</dd>
 <dt>V6</dt><dd>6th simulated covariate</dd>
 <dt>V7</dt><dd>7th simulated covariate</dd>
 <dt>V8</dt><dd>8th simulated covariate</dd>
 <dt>V9</dt><dd>9th simulated covariate</dd>
 <dt>V10</dt><dd>10th simulated covariate</dd>
 <dt>aggregated_outcome</dt><dd>Total number of death in the cluster</dd>
 <dt>aggregated_treatment</dt><dd>Total number of treatment received</dd>
 <dt>number_units</dt><dd>Number of units in each cluster</dd>
 <dt>IV</dt><dd>Cluster-level instrumental variable</dd>
</dl>

Format

A dataset containing the covariates, aggregated outcome,
aggregated treatment received, number of units, and the
cluster-level IV of 100 matched control clusters. There is
a one-to-one correspondence between this 100 matched
control clusters and 100 matched encouraged clusters: the kth
control cluster is matched to the kth encouraged cluster in
<code><a rd-options='' href='encouraged_clusters'>encouraged_clusters</a></code>.

100 matched control clusters — control_clusters

A data frame with 100 rows and 14 columns:<dl class='dl-horizontal'>
 <dt>V1</dt><dd>1st simulated covariate</dd>
 <dt>V2</dt><dd>2nd simulated covariate</dd>
 <dt>V3</dt><dd>3rd simulated covariate</dd>
 <dt>V4</dt><dd>4th simulated covariate</dd>
 <dt>V5</dt><dd>5th simulated covariate</dd>
 <dt>V6</dt><dd>6th simulated covariate</dd>
 <dt>V7</dt><dd>7th simulated covariate</dd>
 <dt>V8</dt><dd>8th simulated covariate</dd>
 <dt>V9</dt><dd>9th simulated covariate</dd>
 <dt>V10</dt><dd>10th simulated covariate</dd>
 <dt>aggregated_outcome</dt><dd>Total number of death in the cluster</dd>
 <dt>aggregated_treatment</dt><dd>Total number of treatment received</dd>
 <dt>number_units</dt><dd>Number of units in each cluster</dd>
 <dt>IV</dt><dd>Cluster-level instrumental variable</dd>
</dl>

control_clusters: 100 matched control clusters

Description

Usage

Arguments

Format