gen_pr_matrix_cluster

Generate condition probability matrix given clusters and probabilities

Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.

Graeme Blair

estimatr

Fast Estimators for Design-Based Inference

Jasper Cooper

Alexander Coppock

Macartan Humphreys

Luke Sonnet

Neal Fultz

Lily Medina

Russell Lenth

gen_pr_matrix_cluster function

<dl><dt>clusters</dt>
<dd>A vector of clusters</dd>
<dt>treat_probs</dt>
<dd>A vector of treatment (condition 2) probabilities</dd>
<dt>simple</dt>
<dd>A boolean for whether the assignment is a random sample
assignment (TRUE, default) or complete random assignment (FALSE)</dd></dl>

Arguments

Generate condition probability matrix given clusters and probabilities — gen_pr_matrix_cluster

<dl>

<dt>clusters</dt>
<dd>A vector of clusters</dd>


<dt>treat_probs</dt>
<dd>A vector of treatment (condition 2) probabilities</dd>


<dt>simple</dt>
<dd>A boolean for whether the assignment is a random sample
assignment (TRUE, default) or complete random assignment (FALSE)</dd>

</dl>

gen_pr_matrix_cluster: Generate condition probability matrix given clusters and probabilities

Description

Usage

Value

Arguments

See Also