Alternative Bootstrap-Based t-Test Aiming to Reduce Type-I Error for Non-Negative, Zero-Inflated Data

Tu & Zhou (1999) showed that comparing the means of populations whose data-generating distributions are non-negative with excess zero observations is a problem of great importance in the analysis of medical cost data. In the same study, Tu & Zhou discuss that it can be difficult to control type-I error rates of general-purpose statistical tests for comparing the means of these particular data sets. This package allows users to perform a modified bootstrap-based t-test that aims to better control type-I error rates in these situations.


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In datasets whose data-generating distributions are non-negative with excess zero observations, it can be difficult to find general-purpose statistical tests for comparing sample means while controlling type-I error rates. This R package allows users to perform a modified bootstrap-based t-test that aims to better control type-I error rates in these particular datasets.

To download and use this package, run the following:

install.packages("devtools") # Unless you already have it
library(devtools)
devtools::install_github("WannabeSmith/rbtt")

To obtain details on how to use the package, run:

help(rbtt)

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install.packages("rbtt")

0.1.0 by Ian Waudby-Smith, a year ago


Browse source code at https://github.com/cran/rbtt


Authors: Ian Waudby-Smith [aut, cre] , Pengfei Li [aut]


Documentation:   PDF Manual  


GPL-3 | file LICENSE license


Imports stats, data.table, parallel


See at CRAN