The BITSS Resource Library contains resources for learning, teaching, and practicing research transparency and reproducibility, including curricula, slide decks, books, guidelines, templates, software, and other tools. All resources are categorized by i) topic, ii) type, and iii) discipline. Filter results by applying criteria along these parameters or use the search bar to find what you’re looking for.
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Stage 1 Registered Report Submission Template Economics and Finance
NRIN Collection of Resources on Research Integrity Data Management and De-identification
PhD Course Materials: Transparent, Open, and Reproducible Policy Research Data Management and De-identification
BITSS Catalyst Sean Grant developed and delivered a PhD course on Transparent, Open, and Reproducible Policy Research at the Pardee RAND Graduate School in Policy Analysis. Find all course materials at the project’s OSF page.
TOP Guidelines InterdisciplinaryTransparent Reporting
Transparency and Openness Promotion (TOP) Guidelines are a set eight modular transparency standards for academic journals, each with three levels of increasing stringency. Journals select which of the eight transparency standards they wish to adopt for their journal, and select a level of implementation for the selected standards. These features provide flexibility for adoption depending on disciplinary variation, but simultaneously establish community standards.
PRISMA is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. PRISMA focuses on the reporting of reviews evaluating randomized trials, but can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions.
SPARC (Scholarly Publishing and Academic Resources Coalition) Data Management and De-identification
This community resource for tracking, comparing, and understanding both current and future U.S. federal funder research data sharing policies is a joint project of SPARC & Johns Hopkins University Libraries.
statcheck Wep App Interdisciplinary
statcheck is a program that checks for errors in statistical reporting in APA-formatted documents. It was originally written in the R programming language. statcheck/web is a web-based implementation of statcheck. Using statcheck/web, you can check any PDF for statistical errors without installing the R programming language on your computer.
NeuroChambers Issues with transparency and reproducibility
Chris Chambers is a psychologist and neuroscientist at the School of Psychology, Cardiff University. He created this blog after taking part in a debate about science journalism at the Royal Institution in March 2012. The aim of his blog is give you some insights from the trenches of science. He talks about a range of science-related issues and may even give up a trade secret or two.
The New Statistics (+OSF Learning Page) Data Management and De-identification
This OSF project helps organize resources for teaching the “New Statistics”–an approach that emphasizes asking quantitative questions, focusing on effect sizes, using confidence intervals to express uncertainty about effect sizes, using modern data visualizations, seeking replication, and using meta-analysis as a matter of course (Cumming, 2011).
statcheck is an R package that checks for errors in statistical reporting in APA-formatted documents. It can help estimate the prevalence of reporting errors and is a tool to check your own work before submitting. The package can be used to automatically extract statistics from articles and recompute p values. It is also available as a wep app.
Manual of Best Practices Dynamic Documents and Coding Practices
Manual of Best Practices, written by Garret Christensen (BITSS), is a working guide to the latest best practices for transparent quantitative social science research. The manual is also available, and occasionally updated on GitHub. For suggestions or feedback, contact firstname.lastname@example.org.
Implementing Reproducible Research Dynamic Documents and Coding Practices
Implementing Reproducible Research by Victoria Stodden, Friedrich Leisch, and Roger D. Peng covers many of the elements necessary for conducting and distributing reproducible research. The book focuses on the tools, practices, and dissemination platforms for ensuring reproducibility in computational science.
Pre-Analysis Plan Template Economics and Finance
Experimental Lab Standard Operating Procedures Data Management and De-identification
This standard operating procedure (SOP) document describes the default practices of the experimental research group led by Donald P. Green at Columbia University. These defaults apply to analytic decisions that have not been made explicit in pre-analysis plans (PAPs). They are not meant to override decisions that are laid out in PAPs. The contents of our lab’s SOP available for public use. We welcome others to copy or adapt it to suit their research purposes.
Standardized Disclosure Peer Review PsychologyTransparent Reporting
A standard statement developed for peer review in psychology.
“I request that the authors add a statement to the paper confirming whether, for all experiments, they have reported all measures, conditions, data exclusions, and how they determined their sample sizes. The authors should, of course, add any additional text to ensure the statement is accurate. This is the standard reviewer disclosure request endorsed by the Center for Open Science [see http://osf.io/project/hadz3]. I include it in every review.”
Zotero InterdisciplinaryTransparent Reporting
Zotero is the only research tool that automatically senses content in your web browser, allowing you to add it to your personal library with a single click. Whether you’re searching for a preprint on arXiv.org, a journal article from JSTOR, a news story from the New York Times, or a book from your university library catalog, Zotero has you covered with support for thousands of sites.
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