PPI Mean Estimation — ppi

Helper function for PPI mean estimation

Usage

ppi_mean(Y_l, f_l, f_u, alpha = 0.05, alternative = "two-sided")

Arguments

Y_l: (vector): n-vector of labeled outcomes.
f_l: (vector): n-vector of predictions in the labeled data.
f_u: (vector): N-vector of predictions in the unlabeled data.
alpha: (scalar): type I error rate for hypothesis testing - values in (0, 1); defaults to 0.05.
alternative: (string): Alternative hypothesis. Must be one of "two-sided", "less", or "greater".

Value

tuple: Lower and upper bounds of the prediction-powered confidence interval for the mean.

Details

Prediction Powered Inference (Angelopoulos et al., 2023) https://www.science.org/doi/10.1126/science.adi6000

Examples


dat <- simdat(model = "mean")

form <- Y - f ~ 1

Y_l <- dat[dat$set == "labeled",   all.vars(form)[1]] |> matrix(ncol = 1)

f_l <- dat[dat$set == "labeled",   all.vars(form)[2]] |> matrix(ncol = 1)

f_u <- dat[dat$set == "unlabeled", all.vars(form)[2]] |> matrix(ncol = 1)

ppi_mean(Y_l, f_l, f_u)
#>          lower    upper
#> [1,] 0.7239045 1.113139