TAILIEUCHUNG - Clarifying ASA’s view on P-values in hypothesis testing

his paper aims at clarifying both the ASA’s Statements on Pvalues (2016) and the recent The American Statistician (TAS) special issue on “Statistical inference in the 21st century: Moving to a world beyond p | Asian Journal of Economics and Banking 2019 3 2 1-16 1 TRƯỜ ự Asian Journal of Economics and Banking ISSN 2588-1396 http . edu .vn Home Clarifying ASA s View on P-Values in Hypothesis Testing William M. Briggs Hung T. Nguyen1 2 1Department of Mathematical Sciences New Mexico State University USA 2Faculty of Economics Chiang Mai University Thailand Article Info Abstract Received 17 01 2019 Accepted 17 06 2019 Available online In Press Keywords Bayesian testing Fisher s significance testing Hypothesis testing LASSO Linear regression Neyman-Pearson s hypothesis test NHST P-values JEL classification C1 C11 C12 MSC2010 classification 62F03 62F15 62J05 This paper aims at clarifying both the ASA s Statements on P-values 2016 and the recent The American Statistician TAS special issue on Statistical inference in the 21st century Moving to a world beyond p 2019 as well as the US National Academy of Science s recent Reproducibility and Replicability in Science 2019 . These documents as a worldwide announcement put a final end to the use of the notion of P-values in frequentist testing of statistical hypotheses. Statisticians might get the impression that abandoning P-values only affects Fisher s significance testing and not Neyman-Pearson s N-P hypothesis testing since these two theories of frequentist testing are different although they are put in a combined testing theory called Null Hypothesis Significance Testing NHST . Such an impression might be gained because the above documents were somewhat silent on N-P testing whose main messages are Don t say statistically significant and Abandon statistical significance . They do not specifically declare The final collapse of the Neyman-Pearson decision theoretic framework as previously presented in Hurlbert and Lombard 14 . Such an impression is dangerous as it might be thought that N-P testing is still valid because P-values are not used per se in it. 1 Corresponding author William M. Briggs Independent Researcher

• Ngân hàng - Tín dụng
• Bayesian testing
• Fisher’s significance testing
• Hypothesis testing
• Linear regression
• Neyman Pearson’s hypothesis test
• P values
• Probability of default
• Credit risk
• PD calibration
• Stress testing
• Low default portfolios
• PD calibration and stress testing
• Error checking
• Survival analysis
• Bayesian methods
• Hematologic Disorders
• Hemolytic Anemia
• Immunologic Tolerance
• Testing effect
• Production effect
• Nonword learning
• Week following training
• Bayesian analysis
• BMC Bioinformatics
• Bayesian shrinkage
• Differentially abundant OTUs
• Phylogeny aware analysis
• Phylogenetic tree