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rbtt  

Alternative Bootstrap-Based t-Test Aiming to Reduce Type-I Error for Non-Negative, Zero-Inflated Data
View on CRAN: Click here


Download and install rbtt package within the R console
Install from CRAN:
install.packages("rbtt")

Install from Github:
library("remotes")
install_github("cran/rbtt")

Install by package version:
library("remotes")
install_version("rbtt", "0.1.0")



Attach the package and use:
library("rbtt")
Maintained by
Ian Waudby-Smith
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-17
Latest Update: 2017-09-17
Description:
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.
How to cite:
Ian Waudby-Smith (2017). rbtt: Alternative Bootstrap-Based t-Test Aiming to Reduce Type-I Error for Non-Negative, Zero-Inflated Data. R package version 0.1.0, https://cran.r-project.org/web/packages/rbtt. Accessed 03 Dec. 2024.
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Some associated functions: rbtt . 
Some associated R codes: rbtt.R .  Full rbtt package functions and examples
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