update_effect: Update the effect in a linearcausalproblem object

In causaloptim: An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects

Update the effect in a linearcausalproblem object

Description

If you want to use the same graph and response function, but change the effect of interest, this can save some computation time.

Usage

update_effect(obj, effectt)

Arguments

obj	An object as returned by analyze_graph
effectt	A character string that represents the causal effect of interest

Value

A object of class linearcausalproblem, see analyze_graph for details

Examples

b <- igraph::graph_from_literal(X -+ Y, X -+ M, M -+ Y, Ul -+ X, Ur -+ Y, Ur -+ M)
V(b)$leftside <- c(1, 0, 0, 1, 0)
V(b)$latent <- c(0, 0, 0, 1, 1)
V(b)$nvals <- c(2, 2, 2, 2, 2)
E(b)$rlconnect <- c(0, 0, 0, 0, 0, 0)
E(b)$edge.monotone <- c(0, 0, 0, 0, 0, 0)
CDE0_query <- "p{Y(M = 0, X = 1) = 1} - p{Y(M = 0, X = 0) = 1}"
CDE0_obj <- analyze_graph(b, constraints = NULL, effectt = CDE0_query)
CDE0_bounds <- optimize_effect_2(CDE0_obj)
CDE0_boundsfunction <- interpret_bounds(bounds = CDE0_bounds$bounds, 
parameters = CDE0_obj$parameters)
CDE1_query <- "p{Y(M = 1, X = 1) = 1} - p{Y(M = 1, X = 0) = 1}"
CDE1_obj <- update_effect(CDE0_obj, effectt = CDE1_query)
CDE1_bounds <- optimize_effect_2(CDE1_obj)
CDE1_boundsfunction <- interpret_bounds(bounds = CDE1_bounds$bounds, 
parameters = CDE1_obj$parameters)

causaloptim documentation built on Oct. 17, 2024, 9:08 a.m.