Censor meta-analytic dataset based on a univariate step-function model

A functional that takes in cut values and weights representing selection probabilities for different intervals of p-values and returns a function that can be used to censor meta-analytic datasets according to the univariate step-function model.

Usage

step_fun(cut_vals = 0.025, weights = 1, renormalize = TRUE)

Arguments

cut_vals

numeric vector of one or more values specifying the threshold (or step) where the selection probability changes.

weights

numeric vector of one or more values specifying the selection probabilities for different intervals of p-values; the intervals are determined by the cut_vals.

renormalize

logical indicating whether to normalize the step function to have a maximum value of 1, with a default value of TRUE.

Value

A function that can be used to censor a meta-analytic dataset based on the univariate step-function model.