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The American statistician, v.73 suppl.1, 2019년, pp.1 - 19
Wasserstein, Ronald L. (American Statistical Association, Alexandria, VA) , Schirm, Allen L. (Mathematica Policy Research (retired), Washington, DC) , Lazar, Nicole A. (Department of Statistics, University of Georgia, Athens, GA)
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Amrhein, Valentin, Trafimow, David, Greenland, Sander. Inferential Statistics as Descriptive Statistics: There Is No Replication Crisis if We Don’t Expect Replication. The American statistician, vol.73, no.suppl1, 262-270.
Anderson, Andrew A.. Assessing Statistical Results: Magnitude, Precision, and Model Uncertainty. The American statistician, vol.73, no.suppl1, 118-121.
Benjamin, Daniel J., Berger, James O.. Three Recommendations for Improving the Use of p -Values. The American statistician, vol.73, no.suppl1, 186-191.
Betensky, Rebecca A.. The p -Value Requires Context, Not a Threshold. The American statistician, vol.73, no.suppl1, 115-117.
Billheimer, Dean. Predictive Inference and Scientific Reproducibility. The American statistician, vol.73, no.suppl1, 291-295.
Blume, Jeffrey D., Greevy, Robert A., Welty, Valerie F., Smith, Jeffrey R., Dupont, William D.. An Introduction to Second-Generation p -Values. The American statistician, vol.73, no.suppl1, 157-167.
Brownstein, Naomi C., Louis, Thomas A., O’Hagan, Anthony, Pendergast, Jane. The Role of Expert Judgment in Statistical Inference and Evidence-Based Decision-Making. The American statistician, vol.73, no.suppl1, 56-68.
Calin-Jageman, Robert J., Cumming, Geoff. The New Statistics for Better Science: Ask How Much, How Uncertain, and What Else Is Known. The American statistician, vol.73, no.suppl1, 271-280.
Campbell, Harlan, Gustafson, Paul. The World of Research Has Gone Berserk: Modeling the Consequences of Requiring “Greater Statistical Stringency” for Scientific Publication. The American statistician, vol.73, no.suppl1, 358-373.
Colquhoun, David. The False Positive Risk: A Proposal Concerning What to Do About p -Values. The American statistician, vol.73, no.suppl1, 192-201.
Fraser, D. A. S.. The p -value Function and Statistical Inference. The American statistician, vol.73, no.suppl1, 135-147.
Fricker Jr., Ronald D., Burke, Katherine, Han, Xiaoyan, Woodall, William H.. Assessing the Statistical Analyses Used in Basic and Applied Social Psychology After Their p -Value Ban. The American statistician, vol.73, no.suppl1, 374-384.
Gannon, Mark Andrew, de Bragança Pereira, Carlos Alberto, Polpo, Adriano. Blending Bayesian and Classical Tools to Define Optimal Sample-Size-Dependent Significance Levels. The American statistician, vol.73, no.suppl1, 213-222.
Goodman, Steven N.. Why is Getting Rid of P -Values So Hard? Musings on Science and Statistics. The American statistician, vol.73, no.suppl1, 26-30.
Goodman, William M., Spruill, Susan E., Komaroff, Eugene. A Proposed Hybrid Effect Size Plus p -Value Criterion: Empirical Evidence Supporting its Use. The American statistician, vol.73, no.suppl1, 168-185.
Greenland, Sander. Valid P -Values Behave Exactly as They Should: Some Misleading Criticisms of P -Values and Their Resolution With S -Values. The American statistician, vol.73, no.suppl1, 106-114.
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Hubbard, Raymond. Will the ASA's Efforts to Improve Statistical Practice be Successful? Some Evidence to the Contrary. The American statistician, vol.73, no.suppl1, 31-35.
Hubbard, Raymond, Haig, Brian D., Parsa, Rahul A.. The Limited Role of Formal Statistical Inference in Scientific Inference. The American statistician, vol.73, no.suppl1, 91-98.
The American Statistician Hurlbert S. 73 2019 Coup de Grâce for a Tough Old Bull: ‘Statistically Significant’ Expires Hurlbert, S., Levine, R., and Utts, J. (2019), “Coup de Grâce for a Tough Old Bull: ‘Statistically Significant’ Expires,” The American Statistician, 73.
Ioannidis, John P. A.. What Have We (Not) Learnt from Millions of Scientific Papers with P Values?. The American statistician, vol.73, no.suppl1, 20-25.
Johnson, Valen E.. Evidence From Marginally Significant t Statistics. The American statistician, vol.73, no.suppl1, 129-134.
Kennedy-Shaffer, Lee. Before p < 0.05 to Beyond p < 0.05: Using History to Contextualize p -Values and Significance Testing. The American statistician, vol.73, no.suppl1, 82-90.
Kmetz, John L.. Correcting Corrupt Research: Recommendations for the Profession to Stop Misuse of p -Values. The American statistician, vol.73, no.suppl1, 36-45.
Lavine, Michael. Frequentist, Bayes, or Other?. The American statistician, vol.73, no.suppl1, 312-318.
Locascio, Joseph J.. The Impact of Results Blind Science Publishing on Statistical Consultation and Collaboration. The American statistician, vol.73, no.suppl1, 346-351.
Manski, Charles F.. Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing. The American statistician, vol.73, no.suppl1, 296-304.
Manski, Charles F., Tetenov, Aleksey. Trial Size for Near-Optimal Choice Between Surveillance and Aggressive Treatment: Reconsidering MSLT-II. The American statistician, vol.73, no.suppl1, 305-311.
Matthews, Robert A. J.. Moving Towards the Post p < 0.05 Era via the Analysis of Credibility. The American statistician, vol.73, no.suppl1, 202-212.
Maurer, Karsten, Hudiburgh, Lynette, Werwinski, Lisa, Bailer, John. Content Audit for p -value Principles in Introductory Statistics. The American statistician, vol.73, no.suppl1, 385-391.
McShane, Blakeley B., Gal, David, Gelman, Andrew, Robert, Christian, Tackett, Jennifer L.. Abandon Statistical Significance. The American statistician, vol.73, no.suppl1, 235-245.
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Pogrow, Stanley. How Effect Size (Practical Significance) Misleads Clinical Practice: The Case for Switching to Practical Benefit to Assess Applied Research Findings. The American statistician, vol.73, no.suppl1, 223-234.
Rose, Sherri, McGuire, Thomas G.. Limitations of P -Values and R -squared for Stepwise Regression Building: A Fairness Demonstration in Health Policy Risk Adjustment. The American statistician, vol.73, no.suppl1, 152-156.
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