Nonparametric Bounds for Regression with Interval-Censored Outcomes
Author: Brenton Kenkel, Vanderbilt University
coefbounds is not yet available on CRAN. To install directly from GitHub:
if (!require("devtools")) {
install.packages("devtools")
library("devtools")
}
devtools::install_github("brentonk/coefbounds", build_vignettes = TRUE)coefbounds is in an early stage of development. Backward-incompatible API changes are possible until version 1.0.0 is released.
Below are some simple usage examples. For more fleshed-out examples, see the package vignette: vignette("introduction", package = "coefbounds").
library("coefbounds")I'll begin by generating some simple data with an interval-censored outcome.
set.seed(97)
x1 <- rnorm(100)
x2 <- rnorm(100)
y <- 1 - x1 + x2 + rnorm(100)
lwr <- floor(y)
upr <- ceiling(y)To estimate coefficient bounds, use coefbounds() with a formula of the form yl + yu ~ x1 + x2 + ..., where yl is the lower bound on each response value and yu is the upper bound.
fit_full <- coefbounds(lwr + upr ~ x1 + x2, boot = 100)
fit_full
#>
#> Call:
#> coefbounds(formula = lwr + upr ~ x1 + x2, boot = 100)
#>
#> Estimated coefficient bounds:
#> lower upper
#> (Intercept) 0.652 1.65
#> x1 -1.247 -0.40
#> x2 0.722 1.48For inference, make sure coefbounds() is run with boot > 0 and use interval_hypothesis() or confint().
interval_hypothesis(fit = fit_full,
term = "x1",
interval = c(0, 0),
type = "subset")
#>
#> Null hypothesis: identification region for x1 contains [0, 0]
#> Estimated identification region: [-1.247, -0.405]
#> Test statistic: sqrt(N) * directed Hausdorff distance
#>
#> stat = 4.05, p-value = <0.01
interval_hypothesis(fit = fit_full,
term = "x2",
interval = c(0.7, 1.6),
type = "equal")
#>
#> Null hypothesis: identification region for x2 equals [0.7, 1.6]
#> Estimated identification region: [0.722, 1.480]
#> Test statistic: sqrt(N) * Hausdorff distance
#>
#> stat = 1.2, p-value = 0.31confint(fit_full, level = 0.99)
#> 0.5 % 99.5 %
#> (Intercept) 0.40717 1.89768
#> x1 -1.47298 -0.17848
#> x2 0.47613 1.72565- Allow clustering in critical value bootstrap.
- Enable parallel processing in bootstrap.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent