query_to_expression

Helper to turn query into a data expression

internal

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

query_to_expression function

<dl><dt>query</dt>
<dd>A character string. An expression defining nodal types to
interrogate <code>realise_outcomes</code>. An expression of the form
"Y[X=1]" asks for the value of Y when X is set to 1</dd>
<dt>node</dt>
<dd>A character string. The quoted name of a node.</dd></dl>

Arguments

Helper to turn query into a data expression — query_to_expression

<dl>

<dt>query</dt>
<dd>A character string. An expression defining nodal types to
interrogate <code>realise_outcomes</code>. An expression of the form
"Y[X=1]" asks for the value of Y when X is set to 1</dd>


<dt>node</dt>
<dd>A character string. The quoted name of a node.</dd>

</dl>

Helper to turn query into a data expression

query_to_expression: Helper to turn query into a data expression

Description

Usage

Value

Arguments