create_effect_vector {causaloptim}

Translate target effect to vector of response variables

Description

Translate target effect to vector of response variables

Usage

create_effect_vector(effect, graph, obsvars, respvars, q.list, variables)

Arguments

effect

Effect list, as returned by parse_effect

graph

The graph

obsvars

Vector of observed variable vertices from the graph

respvars

Response function, as returned by create_response_function

q.list

List with q matrices, as returned by create_q_matrix

variables

Vector of qs names

Value

A list with the target effect in terms of qs

Examples

graph <- graph_from_literal(Z -+ X, X -+ Y, Ul -+ Z, Ur -+ X, Ur -+ Y)
V(graph)$leftside <- c(1, 0, 0, 1, 0)
V(graph)$latent <- c(0, 0, 0, 1, 1)
V(graph)$nvals <- c(3, 2, 2, 2, 2)
V(graph)$exposure <- c(0, 1, 0, 0, 0)
V(graph)$outcome <- c(0, 0, 1, 0, 0)
E(graph)$rlconnect <- c(0, 0, 0, 0, 0)
E(graph)$edge.monotone <- c(0, 0, 0, 0, 0)
constraints <- "X(Z = 1) >= X(Z = 0)"
effectt = "p{Y(X = 1) = 1} - p{Y(X = 0) = 1}"
leftind <- vertex_attr(graph)$leftside
cond.vars <- V(graph)[leftind == 1 & names(V(graph)) != "Ul"]
right.vars <- V(graph)[leftind == 0 & names(V(graph)) != "Ur"] 
obsvars <- c(right.vars, cond.vars)
observed.variables <- V(graph)[V(graph)$latent == 0]
var.values <- lapply(names(observed.variables), 
function(varname) seq(from = 0, to = causaloptim:::numberOfValues(graph, varname) - 1))
names(var.values) <- names(observed.variables)
p.vals <- do.call(expand.grid, var.values)
jd <- do.call(paste0, p.vals[, names(right.vars[right.vars$latent == 0]), drop = FALSE])
cond <- do.call(paste0, p.vals[, names(cond.vars[cond.vars$latent == 0]), drop = FALSE])
parameters <- paste0("p", paste(jd, cond, sep = "_"))
parameters.key <- paste(paste(names(right.vars[right.vars$latent == 0]), collapse = ""), 
paste(names(cond.vars[cond.vars$latent == 0]), collapse = ""), sep = "_")
respvars <- create_response_function(graph, right.vars, cond.vars)
q.list <- create_q_matrix(respvars, right.vars, cond.vars, constraints)
variables <- as.character(unique(q.list$q.vals.all.lookup$vars))
linconstr.list <- create_R_matrix(graph, obsvars, respvars, p.vals, parameters, q.list, variables)
parameters <- linconstr.list$newparams
p.vals <- linconstr.list$newpvals
effect <- parse_effect(effectt)
var.eff <- create_effect_vector(effect, graph, obsvars, respvars, q.list, variables)