strategy_statements

Helper to generate statements of the form "X = 1 &amp; Y = 0" from realized data on one observation

helper

Users can declare binary causal models, update beliefs about causal types given data and calculate arbitrary estimands. Model definition makes use of 'dagitty' functionality. Updating is implemented in 'stan'. The approach used in 'CausalQueries' is a generalization of the 'biqq' models described in "Mixing Methods: A Bayesian Approach" (Humphreys and Jacobs, 2015, <DOI:10.1017/S0003055415000453>). The conceptual extension makes use of work on probabilistic causal models described in Pearl's Causality (Pearl, 2009, <DOI:10.1017/CBO9780511803161>).

Till Tietz

CausalQueries

Make, Update, and Query Binary Causal Models

Clara Bicalho

Jasper Cooper

Macartan Humphreys

Alan Jacobs

Merlin Heidemanns

Lily Medina

Julio Solis

Georgiy Syunyaev

strategy_statements function

<dl><dt>data</dt>
<dd>A data frame with one row</dd>
<dt>strategies</dt>
<dd>A list of strategies where each strategy is a set of nodes to be observed</dd></dl>

Arguments

Generate strategy statements given data — strategy_statements

<dl>

<dt>data</dt>
<dd>A data frame with one row</dd>


<dt>strategies</dt>
<dd>A list of strategies where each strategy is a set of nodes to be observed</dd>

</dl>

Generate strategy statements given data

strategy_statements: Generate strategy statements given data

Description

Usage

Value

Arguments

Examples