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2023

Ball, R.J. (2023). "'Yes We Can!': A Practical Approach to Teaching Reproducibility to Undergraduates." Harvard Data Science Review, 5(3). https://doi.org/10.1162/99608f92.9e002f7b

Bauer, G., Breznau, N., Gereke, J., Höffler, J.H., Janz, N., Rima-Maria, R., Rennstich, J.K., & Soiné, H. (2023). "Teaching Constructive Replications in the Behavioral and Social Sciences Using Quantitative Data." Teaching of Psychology. Available: https://doi.org/10.1177/00986283231219503

Blair, Graeme, Coppock, Alexander, & Humphreys, Macartan. (2023). Research Design in the Social Sciences: Declaration, Diagnosis, and Redesign. Princeton University Press. Available: https://book.declaredesign.org/

Frank, Michael C., et al. (2023). Experimentology: An Open Science Approach to Experimental Psychology Methods. Available: https://experimentology.io/

Underwood, Anthony, Sichel, Aidan & Marshall, Emily C. (2023). "Teaching Reproducible Methods in Economics at Liberal Arts Colleges: A Survey." Journal of Statistics and Data Science Education. https://doi.org/10.1080/26939169.2023.2234425


2022

Ball, Richard B., Medeiros, Norm, Bussberg, Nicholas W., & Piekut, Aneta. (2022). "An Invitation to Teaching Reproducible Research: Lessons from a Symposium." Journal of Statistics and Data Science Education. https://doi.org/10.1080/26939169.2022.2099489

Dogucu, M. & Çetinkaya-Rundel, M. (2022). Tools and Recommendations for Reproducible Teaching, Journal of Statistics and Data Science Education, DOI: 10.1080/26939169.2022.2138645

Domingos, Amanda & Batista, Ian Rebouças (2022). “Um mapa para a transparência e replicabilidade na ciência social empírica: o Protocolo TIER (A Roadmap for Transparency and Replicability in Empirical Social Science: The TIER Protocol).” Revista Politica Hoje. Available: https://periodicos.ufpe.br/revistas/politicahoje/article/view/245776

Lakens, Daniël. (2022). Improving Your Statistical Inferences. https://lakens.github.io/statistical_inferences/index.html

Towse, J., Davies, R., Ball, E., James, R., Gooding, B. & Ivory, M. (2022) LUSTRE: An online data management and student project resource, Journal of Statistics and Data Science Education. DOI: 10.1080/26939169.2022.2118645


2021

Baumer, Benjamin, Kaplan, Daniel, & Horton, Nicholas (2021). Modern Data Science with R. 2nd ed. CRC Press. https://mdsr-book.github.io/mdsr2e/

Bolibaugh, Cylcia, Vanek, Norbert & Marsden, Emma J (2021). Towards a credibility revolution in bilingualism research: Open data and materials as stepping stones to more reproducible and replicable research. Cambridge University Press. https://doi.org/10.1017/S1366728921000535

Bosnjak, Michael et al. (2021). "A template for preregistration of quantitative research in psychology: Report of the Joint Psychological Societies Preregistration Task Force." American Psychologist. http://dx.doi.org/10.1037/amp0000879

Curvale, Carolina & Pérez-Arrobo, Gustavo (2021). “Documentación requerida en revistas de Ciencia Política: hacia prácticas de acceso abierto.” Revista de Ciencia Politica, 41(3). Available: http://ojs.uc.cl/index.php/rcp/article/view/39539

Ingram, Matthew (2021). " Teaching transparency: principles and practical considerations with illustrations in R and Stata." In Teaching Research Methods in Political Science, edited by Jeffrey L. Bernstein, Edward Elgar. https://www.e-elgar.com/shop/usd/teaching-research-methods-in-political-science-9781839101205.html

Sawchuk, S. & Khair, S. (2021). “Computational Reproducibility: A Practical Framework for Data Curators.” Journal of eScience Librarianship, 10(3). Available: https://escholarship.umassmed.edu/jeslib/vol10/iss3/7/

Vilhuber, Lars (2021). "Report by the AEA data editor." American Economic Review Papers and Proceedings, 111: 8-8-17. https://www.aeaweb.org/articles?id=10.1257/pandp.111.808


2020

Blincoe, Sarai & Buchert, Stephanie (2020). "Research preregistration as a teaching and learning tool in undergraduate psychology courses." Psychology Learning & Teaching, 19(1):107-115. https://doi.org/10.1177/1475725719875844

Dekker, Harrison, & Riegelman, Amy (2020). "Advocating for reproducibility." IASSIST Quarterly, 44(2): 1-2. https://doi.org/10.29173/iq982

Gandrud, Christopher (2020). Reproducible Research with R and RStudio, 3rd ed. CRC Press. https://www.routledge.com/Reproducible-Research-with-R-and-RStudio/Gandrud/p/book/9780367143985

Valdez D, Vorland CJ, Brown AW et al. (2020). Improving open and rigorous science: ten key future research opportunities related to rigor, reproducibility, and transparency in scientific research [version 1; peer review: 3 approved]. F1000Research, 9:1235. https://doi.org/10.12688/f1000research.26594.1

Vilhuber, Lars (2020). "Reproducibility and replicability in economics." Harvard Data Science Review, 2(4). https://hdsr.mitpress.mit.edu/pub/fgpmpj1l/release/5?readingCollection=c6cf45bb


2019

Christensen, Garret, Freese, Jeremy, & Miguel, Edward (2019). Transparent and Reproducible Social Science Research. University of California Press. https://www.ucpress.edu/book/9780520296954/transparent-and-reproducible-social-science-research

de la Guardia, Fernando Hoces, & Sturdy, Jennifer (2019). Best Practices for Transparent, Reproducible, and Ethical Research. Inter-American Development Bank. http://dx.doi.org/10.18235/0001564

Dvorak, T., et al. (2019). “Efficient Empiricism: Streamlining Teaching, Research, and Learning in Empirical Courses.” The Journal of Economic Education, 50(3): 242-257. https://doi.org/10.1080/00220485.2019.1618765

Figueiredo, Dalson et al. (2019). "Seven reasons why: a user’s guide to transparency and reproducibility." Brazilian Political Science Review, 13(2). https://doi.org/10.1590/1981-3821201900020001

Lübke, Karsten, Gehrke, Matthias, & Markgraf, Norman (2019). "Statistical Computing and Data Science in Introductory Statistics." In Applications in Statistical Computing, edited by Nadja Bauer et al., Springer. https://link.springer.com/chapter/10.1007/978-3-030-25147-5_9

Madden, Conor. (2019). “Growing Transparency in Research.” Available: https://www.haverford.edu/college-communications/news/growing-transparency-research

Marshall, E. C., & Underwood, A. (2019). “Writing in the discipline and reproducible methods: A process-oriented approach to teaching empirical undergraduate economics research.” The Journal of Economic Education, 50(1), 17–32. https://doi.org/10.1080/00220485.2018.1551100

Marwick, B., Wang, L.-Y., Robinson, R., & Loiselle, H. (2019). "How to Use Replication Assignments for Teaching Integrity in Empirical Archaeology." Advances in Archaeological Practice, 1–9. https://doi.org/10.1017/aap.2019.38

Nurse, A. M., & Staiger, T. (2019). “Teaching Data Reproducibility through Service Learning.” Teaching Sociology, 47(4), 350–357. https://doi.org/10.1177/0092055X19860577

Vilhuber, Lars (2019). "Report by the AEA data editor." American Economic Review Papers and Proceedings, 109: 718-29. https://www.aeaweb.org/articles?id=10.1257/pandp.109.718


2018

Alter, George & Gonzalez, Richard (2018). "Responsible Practices for Data Sharing." American Psychologist, 73(2): 146-156. https://doi.org/10.1037/amp0000258

Baumer, Benjamin (2018). " A Grammar for Reproducible and Painless Extract-Transform-Load Operations on Medium Data." Journal of Computational and Graphical Statistics. https://doi.org/10.1080/10618600.2018.1512867

Berenson, Kathy (2018). Managing Your Research Data and Documentation. American Psychological Association Books. https://www.apa.org/pubs/books/4313048

Christensen, Garret (revised April 24, 2018). "Manual of Best Practices in Transparent Social Science Research." Berkeley Initiative for Transparency in the Social Sciences. https://github.com/garretchristensen/BestPracticesManual/blob/master/Manual.pdf

Christensen, Garret & Miguel, Edward (2018). "Transparency, Reproducibility, and the Credibility of Economics Research." Journal of Economic Literature, 56(3): 920-980. https://www.aeaweb.org/articles?id=10.1257/jel.20171350

Cook, Bryan et al. (2018). "Promoting open science to increase the trustworthiness of evidence in special education." Exception, 85(1):104-118. https://doi.org/10.1177%2F0014402918793138

Marwick, Ben, Boettiger, Carl & Mullen, Lincoln (2018). "Packaging Data Analytical Work Reproducibly Using R (and Friends)." The American Statistician, 72(1): 80-88. https://doi.org/10.1080/00031305.2017.1375986

McNamara, Amelia (2018). "Key Attributes of a Modern Statistical Computing Tool." The American Statistician, 73(4): 375-384. https://doi.org/10.1080/00031305.2018.1482784

Peer, Limor. (2018). “Reproducible Research Practices at ISPS.” Available: https://isps.yale.edu/news/blog/2018/05/reproducible-research-practices-at-isps (Accessed: 29 January 2022).

Vuorre, Matti, & Curley, James (2018). "Curating research assets: A tutorial on the Git version control system." Advances in Methods and Practices in Psychological Science, 1(2): 219-236. https://doi.org/10.1177%2F2515245918754826

Yom, Sean (2018). "Comparative Politics and Area Specialization: The Hidden Costs of Analytic Transparency." Chinese Political Science Review, 1(3): 489-505. https://link.springer.com/article/10.1007/s41111-016-0034-y


2017

Clement, Ryan et al. (2017). "Team-based Data Management Instruction at Small Liberal Arts Colleges." IFLA (International Federation of Library Associations and Institutions) Journal, 43(1): 105-108. https://doi.org/10.1177%2F0340035216678239

Hoeffler, Jan (2017). " ReplicationWiki: Improving Transparency in Social Sciences Research." D-Lib Magazine, 23(3/4): https://doi.org/10.1045/march2017-hoeffler.

McNamara, Amelia, Horton, Nicholas & Baumer, Benjamin (2017). "Greater Data Science at Baccalaureate Institutions." Journal of Computational and Graphical Statistics, 6(4): 781-783. https://doi.org/10.1080/10618600.2017.1386568

Medeiros, Norm & Ball, Richard B. (2017). Teaching Integrity in Empirical Economics: The Pedagogy of Reproducible Science in Undergraduate Education. In M.K. Hensley & S. Davis-Kahl (Eds.), Undergraduate Research and the Academic Librarian: Case Studies and Best Practices. Chicago: Association of College & Research Libraries. Fulltext of chapter


2016

Dekker, Harrison & Lackie, Paula (2016). "Technical Data Skills for Reproducible Research." Chapter 7 in Kellam, Linda & Thompson, Kristi (eds.), Databrarianship: The Academic Data Librarian in Theory and Practice, American Library Association. https://www.alastore.ala.org/content/databrarianship-academic-data-librarian-theory-and-practice

Knittel, Christopher & Metaxoglou, Konstantinos (2016). "Working with Data: Two Empiricists’ Experience." Journal of Econometric Methods, 5(1): 143-152. https://doi.org/10.1515/jem-2016-0001

Vardagan, Mary, Granda, Peter, & Hoelter, Lynette (2016). "Documenting Survey Data Across the Life Cycle." Chapter 29 in Christof Wolf, Dominique Joye, Tom W Smith & Yang-chih Fu (eds.), Sage Handbook of Survey Methodology, Sage Publishing. https://uk.sagepub.com/en-gb/eur/the-sage-handbook-of-survey-methodology/book242251

Yom, Sean (2016). "Analytic transparency, radical honesty, and strategic incentives." PS: Political Science & Politics, 51(2): 416-421. https://doi.org/10.1017/S1049096517002554


2015

Erway, Ricky, et. al. (2015). Building Blocks: Laying the Foundation for a Research Data Management Program. OCLC Research. https://www.oclc.org/research/publications/2016/oclcresearch-data-management-building-blocks-2016.html

Shorish, Yasmeen (2015). "Data Information Literacy and Undergraduates: A Critical Competency." College and Undergraduate Libraries, 22(1): 97-106. https://doi.org/10.1080/10691316.2015.1001246


2014

Owens, Trevor (September 12, 2014). "Teaching Integrity in Empirical Research: An Interview with Richard Ball and Norm Medeiros." The Signal (Blog), US Library of Congress. https://blogs.loc.gov/thesignal/2014/09/teaching-integrity-in-empirical-research-an-interview-with-richard-ball-and-norm-medeiros/.


2012

Ball, Richard B. & Medeiros, Norm. (2012). "Teaching Integrity in Empirical Research: A Protocol for Documenting Data Management and Analysis." Journal of Economic Education, 43(2):182-189. https://doi.org/10.1080/00220485.2012.659647