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[V2-S4] How to Use Statistics Correctly - Understand the Meaning of P Values and Eliminate Misuse
Session Chair(s)
Yoichi M. Ito, PHD
Director, Hokkaido University Hospital, Institute of Health Science Innovation, Japan
There are many statistical perspectives that should be discussed in planning clinical trials and inferring their results. It is necessary to understand statistical methods and results (p value, summary statistics, etc.) correctly. Especially misuse will lead to incorrect interpretation of the results. In The ASA Statement on Statistical Significance and P-values (2016) presented six important principles. Meanwhile, the recommendation on reviewing the advertising method of medical drugs (October 22, 2014: Meeting of Health Labor Science Research Group) suggests about accuracy of product information brochures and advertisements provided by pharmaceutical companies after launch doing. DIA Statistics WS has conducted a statistical workshop for those who are not biostatistics experts engaged in drug development over five times. This session explains the concept of p-value interpretation and statistical methods based on the contents of that statistical workshop. In addition, we introduce points to be noted about the result display in product information brochures and advertisements.
Speaker(s)
Ayano Takeuchi, PHD
5 Faculty of Pharmaceutical Sciences, Keio University, Faculty of Pharmacy, Japan
General Commentary on Misuse of P-Value : According to ASA Statement on P-Values
Moriyuki Miyasato, MBA
Head of Data Science Division, CMIC Co., Ltd., Japan
Pitfalls Surrounding P-Value in Drug Development
Kazumasa Takenouchi
Associate Director, Biostatistics Group, Data Science, Astellas Pharma Inc., Japan
Providing Information on Medical Drugs with Consideration of Evidence Level
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