create_q_matrix

A list of functions as returned by <a rd-options="" href="/link/create_response_function?package=causaloptim&version=0.9.1" data-mini-rdoc="causaloptim::create_response_function">create_response_function</a>

respvars

Vertices of graph on the right side

right.vars

Vertices of graph on the left side

cond.vars

A vector of character strings that represent the constraints

constraints

Translate response functions into matrix of counterfactuals

When causal quantities are not identifiable from the observed data, it still may be possible
to bound these quantities using the observed data. We outline a class of problems for which the
derivation of tight bounds is always a linear programming problem and can therefore, at least
theoretically, be solved using a symbolic linear optimizer. We extend and generalize the
approach of Balke and Pearl (1994) <doi:10.1016/B978-1-55860-332-5.50011-0> and we provide
a user friendly graphical interface for setting up such problems via directed acyclic
graphs (DAG), which only allow for problems within this class to be depicted. The user can
then define linear constraints to further refine their assumptions to meet their specific
problem, and then specify a causal query using a text interface. The program converts this
user defined DAG, query, and constraints, and returns tight bounds. The bounds can be
converted to R functions to evaluate them for specific datasets, and to latex code for
publication. The methods and proofs of tightness and validity of the bounds are described in
a preprint by Sachs, Gabriel, and Sj<c3><b6>lander (2021)
<https://sachsmc.github.io/causaloptim/articles/CausalBoundsMethods.pdf>.

Michael Sachs

causaloptim

An Interface to Specify Causal Graphs and Compute Bounds on
Causal Effects

Michael C Sachs

Erin E Gabriel

Arvid Sj<c3><b6>lander

Gustav Jonzon

Alexander A Balke

Colorado Reed

create_q_matrix function

A list of functions as returned by <a rd-options='' href='create_response_function'>create_response_function</a>

create_q_matrix: Translate response functions into matrix of counterfactuals

Description

Usage

Arguments

Value