knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" )
You can install undi from github with:
# install.packages("devtools") devtools::install_github("jongbinjung/undi")
library(undi) library(tidyverse) inv_logit <- stats::binomial()$linkinv N <- 2000 set.seed(1) data <- tibble(id = rep(1:N)) %>% mutate( m = rnorm(N, 0, 1), x = factor(rep(c("red", "blue"), N / 2)), x = fct_relevel(x, "red"), z = rnorm(N, m, 2), c = rnorm(N, m, 2), e1 = rnorm(N, 0, 0.05), e2 = rnorm(N, 0, 0.05), risk = 1 + 0.05 * (x == "blue") + 0.25 * z + c + e1, a = inv_logit(risk + e2) > .5, y = inv_logit(risk) > .5 )
example_policy <- policy(a ~ x + z + c, data, outcome = "y", cv.folds = 2, distribution = "bernoulli") # Initial RAD computation compute_rad(example_policy) # Sensitivity with uniform parameters sensitivity(example_policy, q = .45, dp = log(1.8), d0 = log(2), d1 = log(1.5)) # Sensitivity with parameters assigned to levels of the grouping variable sensitivity(example_policy, q = c(.45, .55), dp = c(-log(1.2), log(1.5)), d0 = c(-log(3), log(3)), d1 = c(0, log(1.8)) )
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