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Activity Number: 290
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract #311642 View Presentation
Title: Null Hypothesis Significance Testing, Signal Detection Theory, and P<0.05
Author(s): Ming Ji*+
Companies:
Keywords: null hypothesis significance testing ; signal detection theory ; P<0.05 ; alpha level ; ROC curve ; optimal cut point
Abstract:

Null hypothesis significance testing (NHST) has been both a widely used and a highly disputed statistical theory in scientific research. A major complaint about NHST is the arbitrary choice of P< 0.05 as the universal criteria to reject null hypotheses. In this talk, we illustrate the equivalence of the NHST theory and the signal detection theory (SDT) so that the ROC curve methodology originated from SDT can be applied to understand and solve problems in NHST. As a demonstration, the method of determining the (0, 1) optimal cut point on a ROC curve is used to determine the optimal alpha level for the Z test. It is illustrated that an optimal alpha level should be determined for each test with regard to sample size, effect size and cost according to different optimal criteria which include the traditional Neyman-Pearson criteria for a fixed alpha level. Other possible applications of the ROC curve methodology in NHST are further discussed. The clarification of the equivalence of the NHST and the SDT theories contribute to a better understanding of statistical hypothesis testing and scientific research methods in general.


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