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npboottprmFBar
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Install from CRAN:
install.packages("npboottprmFBar")
Install from Github:
library("remotes")
install_github("cran/npboottprmFBar") Install by package version:
library("remotes")
install_version("npboottprmFBar", "0.2.0") Attach the package and use:
library("npboottprmFBar")
Maintained by
Mackson Ncube
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First Published: 2023-12-12
Latest Update: 2024-09-08
Description:
Sample sizes are often small due to hard to reach target populations,
rare target events, time constraints, limited budgets, or ethical considerations.
Two statistical methods with promising performance in small samples are the
nonparametric bootstrap test with pooled resampling method, which is the
focus of Dwivedi, Mallawaarachchi, and Alvarado (2017) ,
and informative hypothesis testing, which is implemented in the 'restriktor'
package. The 'npboottprmFBar' package uses the nonparametric bootstrap test
with pooled resampling method to implement informative hypothesis testing.
The bootFbar() function can be used to analyze data with this method and the
persimon() function can be used to conduct performance simulations on type-one
error and statistical power.
How to cite:
Mackson Ncube (2023). npboottprmFBar: Informative Nonparametric Bootstrap Test with Pooled Resampling. R package version 0.2.0, https://cran.r-project.org/web/packages/npboottprmFBar. Accessed 13 Aug. 2026.
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Complete documentation for npboottprmFBar
Functions, R codes and Examples using
the npboottprmFBar R package
Some associated functions: bootFbar . bootstrap_fbar_sample . persimon .
Some associated R codes: bootFbar.R . persimon.R . Full npboottprmFBar package functions and examples
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