ResProStr package is aimed to provide the functionality for the Research Program Strategy (ResProStr) as explained in the article “Hypothesis-testing demands trustworthy data-a simulation approach to inferential statistics advocating the research program strategy” by Krefeld-Schwalb, Witte & Zenker (2018). The development version of ResProStr package is maintaining by Ozan Evkaya - Ekin Sibel Ceren and feel free to contact for your questions and comments.
With this package, the researchers can reproduce the results mentioned in the following shinny-app
The original research paper:
To install the package from the github repo (Not in CRAN yet), devtools is required and the package can be installed by using following code:
# install.packages("devtools")
# library(devtools)
devtools::install_github("oevkaya/ResProStr")After installing the package from github;
library(ResProStr)ResProStr package provides five easy-to-use functions and attached two more functions for visualization and the summary of the outputs. As an example, samplesH1 function requires four arguments;
Nsample
alpha
effectSize
pow
h1 <- ResProStr::samplesH1(Nsample = 100, alpha = 0.05, effectSize = 0.1, pow = 0.95)From the output of samplesH1 function, estimated sample size is;
h1$NestNon-centrality-parameter of the t-distribution representing H1
h1$ncpFor more detailed calculations, interested reader is referred to the short vignette called Intro_ResProStr.
For any questions and feedback, please don’t hesitate to contact us via following e-mail addresses:
If you use ResProStr package, please cite it:
@Manual{,
title = {ResProStr: An R package for the functionality of the Research Program Strategy (ResProStr)},
author = {Ozan Evkaya, Antonia Krefeld-Schwalb, Frank Zenker, Ekin Ceren},
year = {2022},
note = {R package version 1.0.0},
url = {https://github.com/oevkaya/ResProStr},
}