compute_judgment(): compute a causal judgment. — compute

The general causal judgment function. It is essentially a wrapper over the ces() and ns() functions.

Usage

compute_judgment(var, outcome, causal_model, actual_world, model, s = 0)

Arguments

var: Character string giving the candidate cause variable.
outcome: Character string giving the outcome variable.
causal_model: A named list specifying the causal model.
actual_world: A named list specifying the values of variables in the actual world. The names must match those in causal_model.
model: Character string specifying the causal judgment model. Currently, "ces" and "ns" are supported.
s: Numeric or Named List parameter(s) controlling the adjustment of exogenous variable probabilities toward their actual-world values. Defaults to 0. Usually this is a scalar that applies to all variables in the model, but one can also use a named list that specifies a separate parameter for each variable.

Value

A numeric causal judgment.

Examples

# Define a causal model
causal_model <- list(e = "a & b", a = .1, b = .9)

# Define the actual world
actual_world <- list(e = 1, a = 1, b = 1)

# Compute the CES judgment for A causing E
compute_judgment(
  var = "a",
  outcome = "e",
  causal_model = causal_model,
  actual_world = actual_world,
  model = "ces",
  s = .7
)
#> [1] 0.9472197