Reproducible Research in R: A Tutorial on How to Do the Same Thing More Than Once

Aaron Peikert, Caspar J. van Lissa, Andreas M. Brandmaier

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Computational reproducibility is the ability to obtain identical results from the same data with the same computer code. It is a building block for transparent and cumulative science because it enables the originator and other researchers, on other computers and later in time, to reproduce and thus understand how results came about, while avoiding a variety of errors that may lead to erroneous reporting of statistical and computational results. In this tutorial, we demonstrate how the R package repro supports researchers in creating fully computationally reproducible research projects with tools from the software engineering community. Building upon this notion of fully automated reproducibility, we present several applications including the preregistration of research plans with code (Preregistration as Code, PAC). PAC eschews all ambiguity of traditional preregistration and offers several more advantages. Making technical advancements that serve reproducibility more widely accessible for researchers holds the potential to innovate the research process and to help it become more productive, credible, and reliable.
Original languageEnglish
Pages (from-to)836-867
Number of pages32
JournalPsych
Volume3
Issue number4
DOIs
Publication statusPublished - Sept 2021
Externally publishedYes

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