What population skill a reported level is consistent with

tss_inflation() maps a population skill to the level a design reports for it. This inverts that map: given a level actually read off a ladder, it solves for the population skill whose expected reported level equals it.

Usage

implied_skill(
  y,
  folds,
  observed,
  grid = seq(0, 0.95, by = 0.05),
  replicates = 200L,
  seed = 1L
)

Arguments

y

The response: a matrix or data frame of units by variables, with unit identifiers in the row names or in a leading character or factor column.

folds

A fold map from fold_map(), or any named integer vector of the same shape.

observed

Reported levels to invert.

grid

Population skills the forward map is measured on before interpolating between them.

replicates

Replicates per value.

seed

Random seed.

Value

A data frame of one row per observed level: the level, the population skill it is consistent with, and whether that sits inside the grid the map was measured on.

Details

It answers the question a level raises once the inflation is known, under the distribution of predictions tss_inflation() plants; a model whose predictions are distributed otherwise is inflated by a different amount. It does not correct a difference between two arms, whose inflations need not be equal.

Examples

set.seed(1)
y <- matrix(rbinom(1200, 1, 0.15), nrow = 200,
            dimnames = list(sprintf("p%03d", 1:200), paste0("sp", 1:6)))
implied_skill(y, fold_map(y, v = 5), observed = 0.71, replicates = 40)