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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IEEE DataPort Data RepositoriesMetascience (Methods and Archival Science)Open PublishingReproducibility
PGRP Onboarding Materials for Collaborative Reproducible Workflows Data ManagementEconomicsInterdisciplinaryPolitical ScienceReproducibilityVersion Control
Catalyst Thomas Brailey developed a set of training materials to help transition J-PAL’s Payments and Governance Research Program (PGRP) towards a version-controlled research pipeline by onboarding all research team members to GitHub, GitHub desktop, and R. These teaching materials can be applied to onboard other research/lab teams across a variety of contexts in social science research.
Coding style guides for collaborators (in R, Stata, and Python) Dynamic Documents and Coding PracticesInterdisciplinaryReproducibility
Developed by Sean Higgins (Northwestern University) and colleagues, this guide provides instructions for using R on research projects. Its purpose is to use with collaborators and research assistants to make code consistent, easier to read, transparent, and reproducible. See also the Python Guide and Stata Guide.
Social Science Reproduction Platform EconomicsIssues with transparency and reproducibilityMetascience (Methods and Archival Science)Other Social SciencesPolitical SciencePsychologyPublic HealthPublic PolicyReplicationsReproducibilitySociologyStatistics and Data Science
The Social Science Reproduction Platform crowdsources and catalogs attempts to assess and improve the computational reproducibility of social science research. Instructors can use the SSRP in applied social science courses at the graduate or undergraduate levels to teach fundamental concepts, methods, and reproducible research practices. Get started by creating a free account and browsing some of the completed reproductions! Instructors can start by reviewing the guide for instructors, which contains tips and resources for teaching and grading reproductions using the platform.
A template README for social science replication packages Data ManagementEconomicsInterdisciplinaryOther Social SciencesPolitical SciencePsychologyPublic HealthPublic PolicyReproducibility
The template README follows best practices as defined by a number of data editors at social science journals. A full list of endorsers is listed in Endorsers. The most recent version is available at https://social-science-data-editors.github.io/template_README/. Specific releases can be found at https://github.com/social-science-data-editors/template_README/releases. The template README is available in a variety of formats, including HTML (best for reading), LaTeX, Word, PDF, and Markdown.
Lab Manual for Jade Benjamin-Chung’s Lab Data ManagementInterdisciplinaryPublic HealthReproducibility
ResearchBox Data ManagementInterdisciplinary
ResearchBox offers an easy way to share and access scientific content, such as data, code, pre-registrations, and study materials. Uploaded files are organized into “Bingo Tables” that allow readers to easily find & access available files (e.g., researchbox.org/15). Among many features, ResearchBox provides:
- One-click downloads
- Instantaneous file-previews
- Codebooks for every dataset
- Integration with AsPredicted.org
Development Research in Practice : The DIME Analytics Data Handbook Data ManagementEconomicsEthicsImpact EvaluationInterdisciplinaryInternational DevelopmentPre-Analysis PlansPre-RegistrationStatistical Literacy
“Development Research in Practice” leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data on how to handle data effectively, efficiently, and ethically. See an accompanying online course here.
An Introduction to Open Science InterdisciplinaryOpen Science
This presentation by Felix Schönbrodt gives an overview of the motivation for open science and an introduction to the research tools and practices commonly associated with open science. The slides are can be re-used and distributed under the CC BY license.
Reproducible Data Science with Python Data VisualizationInterdisciplinaryReproducibilityStatistics and Data ScienceVersion Control
Written by Valentin Danchev, “Reproducible Data Science with Python” is a textbook that uses real-world social data sets related to the COVID-19 pandemic to provide an accessible introduction to open, reproducible, and ethical data analysis using hands-on Python coding, modern open-source computational tools, and data science techniques. Topics include open reproducible research workflows, data wrangling, exploratory data analysis, data visualization, pattern discovery (e.g., clustering), prediction & machine learning, causal inference, and network analysis.
Framework for Open and Reproducible Research Training (FORRT) Data ManagementDynamic Documents and Coding PracticesInterdisciplinaryIssues with transparency and reproducibilityPre-Analysis PlansStatistical LiteracyTransparent Reporting
FORRT is a pedagogical infrastructure designed to recognize and support the teaching and mentoring of open and reproducible science tenets in tandem with prototypical subject matters in higher education. FORRT also advocates for the opening of teaching and mentoring materials as a means to facilitate access, discovery, and learning to those who otherwise would be educationally disenfranchised.
Dataverse: Research Transparency through Data Sharing Data RepositoriesReproducibilityTransparency
Find slides from a presentation by Mercè Crosas titled “Dataverse: Research Transparency through Data Sharing”.
Reporting Standards for Social Science Experiments Social ScienceTransparent Reporting
Find slides from a presentation by Kevin Esterling titled “Reporting Standards for Social Science Experiments”.
What Scholars and Citizens Think of Experimental Ethics EthicsInterdisciplinaryOther Social Sciences
Find slides from a presentation by Scott Desposato titled “What Scholars and Citizens Think of Experimental Ethics: Results of a Survey Experiment”.
Framing Transparency in Research: Issues and Opportunities Issues with transparency and reproducibilityTransparency
Find slides from a presentation by Victoria Stodden titled “Framing Transparency in Research: Issues and Opportunities”.
Find slides from a presentation by Edward Miguel titled “BITSS Overview and Introduction to 2015 Annual Meeting”.
False-Positives, p-Hacking, Power, and Evidential Value Statistics and Data Science
Find slides from a presentation by Leif Nelson titled “False-Positives, p-Hacking, Power, and Evidential Value”.
S-values: Conventional measures of the sturdiness of the signs regression coefficients Statistics and Data Science
Find slides from a presentation by Ed Leamer titled “S-values: Conventional measures of the sturdiness of the signs regression coefficients”.
Reproducible and Collaborative Statistical Data Science Pre-Analysis Plans
Find slides from a presentation by Philip Stark titled “Reproducible and Collaborative Statistical Data Science”.
Registration and Version Control with OSF & GitHub RegistriesVersion Control
Find slides from a presentation by Garret Christensen titled “Registration and Version Control with OSF & GitHub”.
Investigation of Data-Sharing Attitudes in the Context of a Meta-Analysis Metascience (Methods and Archival Science)Statistics and Data Science
Find slides from a presentation by Joshua Polanin titled “Investigation of Data-Sharing Attitudes in the Context of a Meta-Analysis”.
The Strength of Evidence from Statistical Significance and P-values Statistics and Data Science
Find slides from a presentation by Dan Benjamin titled “The Strength of Evidence from Statistical Significance and P-values”.
Pre-Analysis Plans in Behavioral and Experimental Economics EconomicsPre-Analysis Plans
Find slides from a presentation by Johannes Haushoffer titled “Pre-Analysis Plans in Behavioral and Experimental Economics”.
Handbook on Using Administrative Data for Research and Evidence-Based Policy Data ManagementEconomicsInterdisciplinaryInternational DevelopmentReproducibility
Co-edited by Shawn Cole, Iqbal Dhaliwal, Anja Sautmann, and Lars Vilhuber and published by J-PAL’s Innovations in Data and Experiments for Action Initiative (IDEA), this handbook includes case studies of large-scale randomized evaluations using private and national government administrative data, and technical guidance to support partnerships with governments, nonprofits, or firms to access data and pursue cutting-edge, policy-relevant projects.
Survey of Registered Reports Editors InterdisciplinaryResults-Blind Review & Registered Reports
Between December 15, 2017 and January 31, 2018, BITSS surveyed the editors of 76 academic journals which at the time, accepted submissions in the Registered Report (RR) format. Find summary statistics of the results in this document.
CRediT (Contributor Roles Taxonomy) InterdisciplinaryTransparent Reporting
CRediT (Contributor Roles Taxonomy) is high-level taxonomy, including 14 roles, that can be used to represent the roles typically played by contributors to scientific scholarly output. The roles describe each contributor’s specific contribution to the scholarly output.
Comparison of multiple hypothesis testing commands in Stata EconomicsStatistics and Data Science
In this post on the Development Impact blog, David McKenzie (World Bank) compares various Stata packages used for multiple hypothesis testing adjustments and discusses settings where each package is best applied.
Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Educational Expansion EpidemiologyStatistical LiteracyTransparent Reporting
Created by Catalyst Melissa Sharp, this is an open-source repository for epidemiological research methods and reporting skills for observational studies, structured based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement. Use it to discover new methods and reporting guidelines and contribute through the GitHub repository (https://github.com/sharpmel/STROBECourse/).
Pre-Analysis Plans for Observational Research EconomicsPre-Analysis Plans
In her presentation at RT2 DC in 2019, Fiona Burlig (University of Chicago) provides advice on how one can credibly pre-register an observational research project. Also see Burlig’s 2018 paper that describes three scenarios for pre-registration of observational work, including i) cases where researchers collect their own data; ii) prospective studies; and iii) research using restricted-access data.