Resources

Workshop goals - Why are we teaching this - Why is this important - For future and current you - For research as a whole - Lack of reproducibility in research is a real problem Materials and how we'll use them - Workshop landing page, with - links …

An introduction to managing, annotating, organizing, archiving, and publishing research data using the Open Science Framework.

Confirmation through competent replication is a founding principle of modern science. However, biomedical researchers are rewarded for innovation, and not for confirmation, and confirmatory research is often stigmatized as unoriginal and as a …

This list of resources consists of resources for researchers, editors, and reviewers interested in practicing open science principles, particularly in education research. This list is not exhaustive but meant as a starting point for individuals …

The information provided on this website is designed to assist the extramural community in addressing rigor and transparency in NIH grant applications and progress reports. Scientific rigor and transparency in conducting biomedical research is key to …

Efforts to Instill the Fundamental Principles of Rigorous ResearchRigorous experimental procedures and transparent reporting of research results are vital to the continued success of the biomedical enterprise at both the preclinical and the clinical …

The reliability of experimental findings depends on the rigour of experimental design. Here we show limited reporting of measures to reduce the risk of bias in a random sample of life sciences publications, significantly lower reporting of …

RStudio Cheatsheets The cheatsheets below make it easy to use some of our favorite packages. Cheatsheets include the following topics: Python with R and Reticulate Cheatsheet: The reticulate package provides a comprehensive set of tools for …

An academic scientist’s professional success depends on publishing. Publishing norms emphasize novel, positive results. As such, disciplinary incentives encourage design, analysis, and reporting decisions that elicit positive results and ignore …

Preregistration is the process of specifying project details, such as hypotheses, data collection procedures, and analytical decisions, prior to conducting a study. It is designed to make a clearer distinction between data-driven, exploratory work …