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Causal weight accessors

Source: R/causal-weights.R
causal-weights.Rd

Generics for inspecting and setting the metadata carried by causal weight vectors.

  • is_causal_wt() tests whether an object is a causal weight vector.

  • estimand() returns the causal estimand the weights target, such as "ate" or "att".

  • estimand<-() sets the causal estimand.

Usage

is_causal_wt(x, ...)

estimand(x, ...)

estimand(x, ...) <- value

Arguments

x

An object to inspect or modify. These generics dispatch on this argument.

...

Arguments passed to methods.

value

The causal estimand to assign.

Value

is_causal_wt() returns a single logical value. estimand() returns the estimand, typically a character string, or NULL when none is recorded. estimand<-() returns x with the estimand updated.

Details

This package defines the generics and the abstract weight class they are written against. It supplies a method for each generic on causal_wts, so a concrete class built with new_causal_wts() inherits all three. The concrete classes themselves live in the packages that own them, such as propensity, as do methods for any object that is not a causal_wts vector. is_causal_wt() defaults to FALSE so that any object that is not a recognized causal weight vector reports as much; estimand() and estimand<-() have no meaningful default and signal an error when no method is registered for the object.

See also

new_causal_wts() for the class these generics have methods for, and the propensity package for concrete weight classes. ipw() estimates an effect from a set of weights, and the result it returns answers estimand() with the estimand those weights targeted, so the same accessor reads the weights and the estimate made from them.

Examples

wts <- new_causal_wts(
  c(1.2, 0.8, 1.5),
  subclass = "cg_toy_wts",
  estimand = "ate"
)

is_causal_wt(wts)
#> [1] TRUE
estimand(wts)
#> [1] "ate"

# The estimand is metadata on the vector, so it can be replaced in place.
estimand(wts) <- "att"
estimand(wts)
#> [1] "att"

# An object that is not a causal weight vector reports `FALSE` rather than
# erroring.
is_causal_wt(1:3)
#> [1] FALSE

# `estimand()` has no meaningful default, so it errors instead.
try(estimand(1:3))
#> Error in estimand.default(1:3) : 
#>   No `estimand()` method for an object of class <integer>.