GitHub - SamCH93/ciCalibrate: R package for computing support intervals for univariate parameters based on confidence intervals or parameter estimates with standard errors. (original) (raw)
ciCalibrate
ciCalibrate is an R package for computing support intervals for unknown univariate parameters. A support interval can either be computed based on a parameter estimate and standard error or based on a confidence interval for the respective parameter. The main function for doing so is ciCalibrate
, see the documentation with ?ciCalibrate
for the available options. Theoretical background on support intervals is provided in the accompanying paper Pawel et al. (2023) and also Wagenmakers et al. (2020).
Installation
development version from GitHub (requires remotes package)
remotes::install_github(repo = "SamCH93/ciCalibrate")
from CRAN
install.packages(pkgs = "ciCalibrate")
Usage
library("ciCalibrate")
data from RECOVERY trial
logHR <- -0.19 # estimate se <- 0.05 # standard error of estimate ci95 <- logHR + c(-1, 1) * qnorm(p = 0.975) * se # 95% Wald-CI
default normal prior for logHR under the alternative H1
pm <- 0 # center around value of no effect psd <- 2 # unit-information standard deviation for a logHR
compute a support interval with support level = 10
si10 <- ciCalibrate(estimate = logHR, se = se, siLevel = 10, method = "SI-normal", priorMean = pm, priorSD = psd)
compute instead with confidence interval as input
si10 <- ciCalibrate(ci = ci95, ciLevel = 0.95, siLevel = 10, method = "SI-normal", priorMean = pm, priorSD = psd) si10
#> Point Estimate [95% Confidence Interval] #> -0.19 [-0.29,-0.092] #> #> Calibration Method #> Normal prior for parameter under alternative #> with mean m = 0 and standard deviation sd = 2 #> #> k = 10 Support Interval #> [-0.27,-0.11]
plot Bayes factor function and support interval
plot(si10)
References
Pawel, S., Ly, A., and Wagenmakers, E.-J. (2023). Evidential Calibration of Confidence Intervals. The American Statistician.doi:10.1080/00031305.2023.2216239
- Wagenmakers, E.-J., Gronau, Q. F., Dablander, F., and Etz, A. (2020). The support interval. Erkenntnis.doi:10.1007/s10670-019-00209-z