Find books and articles that cite Project TIER
2025
Skubera, M., Korbmacher, M., Evans, T. R., Azevedo, F., & Pennington, C.R. (2025). International initiatives to enhance awareness and uptake of open research in psychology: A systematic mapping review. Royal Society Open Science, 12(3): 241726. https://doi.org/10.1098/rsos.241726
Swannack, T. M., Cushway, K. C., Carrillo, C. C., Calvo, C., Determan, K. R., Mierzejewski, C. M., Quintana, V. M., Riggins, C. L., Sams, M. D., & Wadsworth, W. E. (2025). Cracking the code: Linking good modeling and coding practices for new ecological modelers. Ecological Modelling, 499, 110926. https://doi.org/10.1016/j.ecolmodel.2024.110926
2024
Dogucu, M. (2024). Reproducibility in the classroom. Annual Review of Statistics and Its Application. 12:89-105. https://doi.org/10.1146/annurev-statistics-112723-034436
Furlong, D. E., Romero, A., Helström, K., Lester, J. N., & Karcher, S. (2024). Teaching with shared data for learning qualitative data analysis: A multi-sited case study of instructor and student experiences. International Journal of Research & Method in Education, 1–15. https://doi.org/10.1080/1743727X.2024.2443935
Horton, N. J., & Stoudt, S. (2024). Editorial: Guidelines and best practices to share deidentified data and code. Journal of Statistics and Data Science Education, 32(3): 227–231. https://doi.org/10.1080/26939169.2024.2364737
Gidakovic, S. (2024). Librarian support in teaching open science research practices in higher education. Issues in Science and Technology Librarianship, (107). https://doi.org/10.29173/istl2791
Gligorić, K., Piccardi, T., Hofman, J. M., & West, R. (2024). In-class data analysis replications: Teaching students while testing science. Harvard Data Science Review, 6(3).https://doi.org/10.1162/99608f92.f9720d1f
Ostermann, F. O. (2024). Educating for Open and Reproducible Research in the Geosciences: Lessons from an MSc program. AGILE: GIScience Series, 5, 43. https://doi.org/10.5194/agile-giss-5-43-2024
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
Bean, B. L. (2023). “Teaching reproducibility to first year college students: Reflections from an introductory data science course,” Journal on Empowering Teaching Excellence, 7(2): Article 5. https://doi.org/10.26077/5978-0434
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/
Homewood, C. (2023, August 2). Investigating Issues with Reproducibility in Journal Articles Published in Psychological Science. https://doi.org/10.31234/osf.io/6d5nq
Mendez-Carbajo, D., & Dellachiesa, A. (2023). Choice of data visualization tool: FRED or spreadsheets? International Review of Economics Education, 44, 100275. https://doi.org/10.1016/j.iree.2023.100275
Pruim, R., Gîrjău, M.-C., & Horton, N. J. (2023). Fostering better coding practices for data scientists. Harvard Data Science Review, 5(3). https://doi.org/10.1162/99608f92.97c9f60f
Siddiqui, N. (2023). Minimal research compendiums: An approach to advance statistical validity and reproducibility in digital humanities research. International Journal of Digital Humanities, 5(2–3): 405–429. https://doi.org/10.1007/s42803-023-00074-x
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
Vilhuber, L., Schmutte, I., Michuda, A., & Connolly, M. (2023). Reinforcing reproducibility and replicability: An introduction. Harvard Data Science Review, 5(3). https://doi.org/10.1162/99608f92.9ba2bd43
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
Janz, N., & Freese, J. (2021). Replicate others as you would like to be replicated yourself. PS: Political Science & Politics, 54(2): 305–308. https://doi.org/10.1017/S1049096520000943
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
Geiger, R. S., Yu, K., Yang, Y., Dai, M., Qiu, J., Tang, R., & Huang, J. (2020). Garbage in, garbage out?: Do machine learning application papers in social computing report where human-labeled training data comes from? Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 325–336. https://doi.org/10.1145/3351095.3372862
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
Dan Sholler, Diya Das , Fernando Hoces de la Guardia, Chris Hoffmann, François Lanusse, Nelle Varoquaux, Rolando Garcia, R. Stuart Geiger, Shana McDevitt, Scott Peterson, Sara Stoudt. “Best Practices for Managing Turnover in Data Science Groups, Teams, and Labs.” BIDS Best Practices in Data Science Series. Berkeley,CA: Berkeley Institute for Data Science. 2019. https://doi.org/10.31235/osf.io/wsxru
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
Halliday, S. D. (2019). Promoting an ethical economics classroom through partnership. International Journal for Students as Partners, 3(1): 182–189. https://doi.org/10.15173/ijsap.v3i1.3623
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
Burkett, J. P. (2018). Introduction to Reproducible Research in Social Sciences. 10.13140/RG.2.2.24016.56327.
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