3-hour interactive presentation. 8 lessons include and continue the Meeting version. Subsequent lessons teach additional methods for estimating sample size with and without pilot data, targeting p-values or other criteria. Participants learn how to evaluate external resources before applying them, then finally consider the role of communication about sample size as a key determinant of certainty in scientific interpretation. Teach one week of class, or run an intensive workshop.
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References:
Sample Size
Albers, C. (2019). The problem with unadjusted multiple and sequential statistical testing. Nature Communications, 10(1), 1921. https://doi.org/10.1038/s41467-019-09941-0
Bazerman, M. H., & Samuelson, W. F. (1983). I won the auction but don’t want the prize. Journal of Conflict Resolution, 27(4), 618–634.
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013). Power failure: Why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14(5), 365–376. https://doi.org/10.1038/nrn3475
Cohen, J. (1977). Statistical Power Analysis for the Behavioral Sciences. Elsevier Science & Technology. https://ebookcentral-proquest-com.proxy.library.upenn.edu/lib/upenn-ebooks/detail.action?docID=1882849
Danziger, M., Collazo, A., Dirnagl, U., & Toelch, U. (2022). Balancing sensitivity and specificity in preclinical research (p. 2022.01.17.476585). bioRxiv. https://doi.org/10.1101/2022.01.17.476585
Efron, B., & Tibshirani, R. J. (1994). An Introduction to the Bootstrap. Chapman and Hall/CRC. https://doi.org/10.1201/9780429246593
Hesterberg, T. C. (2015). What Teachers Should Know About the Bootstrap: Resampling in the Undergraduate Statistics Curriculum. The American Statistician, 69(4), 371–386. https://doi.org/10.1080/00031305.2015.1089789
Hoenig, J. M., & Heisey, D. M. (2001). The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis. The American Statistician, 55(1), 19–24. https://doi.org/10.1198/000313001300339897
Johnson, P. C. D., Barry, S. J. E., Ferguson, H. M., & Müller, P. (2015). Power analysis for generalized linear mixed models in ecology and evolution. Methods in Ecology and Evolution, 6(2), 133–142. https://doi.org/10.1111/2041-210X.12306
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Lazic, S. E. (2022). Genuine replication and pseudoreplication. Nature Reviews Methods Primers, 2(1), 23. https://doi.org/10.1038/s43586-022-00114-w
Lazic, S. E., Clarke-Williams, C. J., & Munafò, M. R. (2018). What exactly is ‘N’ in cell culture and animal experiments? PLOS Biology, 16(4), e2005282. https://doi.org/10.1371/journal.pbio.2005282
Reinagel, P. (2023). Is N-Hacking Ever OK? The consequences of collecting more data in pursuit of statistical significance. PLOS Biology, 21(11), e3002345. https://doi.org/10.1371/journal.pbio.3002345
Savitz, D. A., Wise, L. A., Bond, J. C., Hatch, E. E., Ncube, C. N., Wesselink, A. K., Willis, M. D., Yland, J. J., & Rothman, K. J. (2024). Responding to Reviewers and Editors About Statistical Significance Testing. Annals of Internal Medicine, 177(3), 385–386. https://doi.org/10.7326/M23-2430
Sert, N. P. du, Ahluwalia, A., Alam, S., Avey, M. T., Baker, M., Browne, W. J., Clark, A., Cuthill, I. C., Dirnagl, U., Emerson, M., Garner, P., Holgate, S. T., Howells, D. W., Hurst, V., Karp, N. A., Lazic, S. E., Lidster, K., MacCallum, C. J., Macleod, M., … Würbel, H. (2020). Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0. PLOS Biology, 18(7), e3000411. https://doi.org/10.1371/journal.pbio.3000411
Walters, S. J. (2004). Sample size and power estimation for studies with health related quality of life outcomes: A comparison of four methods using the SF-36. Health and Quality of Life Outcomes, 2, 26. https://doi.org/10.1186/1477-7525-2-26