Many scientific fields are facing a reproducibility crisis, revealed where replication fails to reproduce findings from previous work. This irreproducibility leads to the promulgation of inappropriate evidence.
In this article, we present a model for determining how total research payoff depends on researchers’ choices of sample sizes, α levels, and other parameters of the research process. The model can be used to quantify various tradeoffs inherent in the …
This is an introductory guide for those working and considering working in the area of open research. It was drafted by members of the Open Research Competencies Coalition. There are many resources available on the topic of open research either aimed …
Qualitative training rarely acknowledges the role of emotions in both data collection and analysis. While bracketing emotions is an important part of reflexivity, emotions are both a source of data and a source of ‘work’ (Hochschild, Citation1983). …
Getting started with open science and knowing where to go. This webinar will introduce participants to major practices in open science and then dive into the resources available to learn how to use these in your own work.
Because scientists tend to report only studies (publication bias) or analyses (p-hacking) that “work,” readers must ask, “Are these effects true, or do they merely reflect selective reporting?” We introduce p-curve as a way to answer this question. …