Check if propensity scores have been refit

is_refit() tests whether x is a ps_trim object whose propensity model has been refit on the retained (non-trimmed) observations via ps_refit().

Usage

is_refit(x)

Arguments

x

An object to test (typically a ps_trim vector).

Value

A single TRUE or FALSE.

Details

On a psw vector built from trimmed propensity scores, the answer comes from the trimming record carried on the weights. is_refit() reads a single flag out of that record rather than a position, so unlike is_unit_trimmed() it answers from any record present, whatever length the weights have since taken on. It raises an error of class propensity_missing_meta_error only when weights marked as trimmed carry no record at all, which is what a subset of such weights leaves behind. Weights that were never trimmed have nothing missing and return FALSE.

See also

ps_refit() to refit a propensity model after trimming, ps_trim() to trim propensity scores.

Examples

set.seed(2)
n <- 30
x <- rnorm(n)
z <- rbinom(n, 1, plogis(0.4 * x))
fit <- glm(z ~ x, family = binomial)
ps <- predict(fit, type = "response")

trimmed <- ps_trim(ps, lower = 0.2, upper = 0.8)
is_refit(trimmed)
#> [1] FALSE

refit <- ps_refit(trimmed, fit)
is_refit(refit)
#> [1] TRUE