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Statistics With Posterior Probability And A Phc Curve


Statistics With Posterior Probability And A Phc Curve
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Statistics With Posterior Probability And A Phc Curve


Statistics With Posterior Probability And A Phc Curve
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Author : Hideki Toyoda
language : en
Publisher: Springer Nature
Release Date : 2024

Statistics With Posterior Probability And A Phc Curve written by Hideki Toyoda and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Markov processes categories.


This textbook reconstructs the statistics curriculum from the perspective of posterior probability. In recent years, there have been several reports that the results of studies using significant tests cannot be reproduced. It is a problem called a "reproducibility crisis". For example, suppose we could reject the null hypothesis that "the average number of days to recovery in patients who took a new drug was the same as that in the control group". However, rejecting the null hypothesis is only a necessary condition for the new drug to be effective. Even if the necessary conditions are met, it does not necessarily mean that the new drug is effective. In fact, there are many cases where the effect is not reproduced. Sufficient conditions should be presented, such as "the average number of days until recovery in patients who take new drugs is sufficiently short compared to the control group, evaluated from a medical point of view", without paying attention to necessary conditions. This book reconstructs statistics from the perspective of PHC, i.e., probability that a research hypothesis is correct. For example, the PHC curve shows the posterior probability that the statement "The average number of days until recovery for patients taking a new drug is at least days shorter than that of the control group" is correct as a function of . Using the PHC curve makes it possible to discuss the sufficient conditions rather than the necessary conditions for being an efficient treatment. The value of statistical research should be evaluated with concrete indicators such as "90% probability of being at least 3 days shorter", not abstract metrics like the p-value.



Statistics With Posterior Probability And A Phc Curve


Statistics With Posterior Probability And A Phc Curve
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Author : Hideki Toyoda
language : en
Publisher: Springer
Release Date : 2024-07-22

Statistics With Posterior Probability And A Phc Curve written by Hideki Toyoda and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Social Science categories.


This textbook reconstructs the statistics curriculum from the perspective of posterior probability. In recent years, there have been several reports that the results of studies using significant tests cannot be reproduced. It is a problem called a “reproducibility crisis”. For example, suppose we could reject the null hypothesis that “the average number of days to recovery in patients who took a new drug was the same as that in the control group”. However, rejecting the null hypothesis is only a necessary condition for the new drug to be effective. Even if the necessary conditions are met, it does not necessarily mean that the new drug is effective. In fact, there are many cases where the effect is not reproduced. Sufficient conditions should be presented, such as “the average number of days until recovery in patients who take new drugs is sufficiently short compared to the control group, evaluated from a medical point of view”, without paying attention to necessary conditions. This book reconstructs statistics from the perspective of PHC, i.e., probability that a research hypothesis is correct. For example, the PHC curve shows the posterior probability that the statement “The average number of days until recovery for patients taking a new drug is at least θ days shorter than that of the control group” is correct as a function of θ. Using the PHC curve makes it possible to discuss the sufficient conditions rather than the necessary conditions for being an efficient treatment. The value of statistical research should be evaluated with concrete indicators such as “90% probability of being at least 3 days shorter”, not abstract metrics like the p-value.



Statistical Significance And The Phc Curve


Statistical Significance And The Phc Curve
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Author : Hideki Toyoda
language : en
Publisher: Springer Nature
Release Date : 2024-10-28

Statistical Significance And The Phc Curve written by Hideki Toyoda and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-28 with Social Science categories.


This book explains the importance of using the probability that the hypothesis is correct (PHC), an intuitive measure that anyone can understand, as an alternative to the p-value. In order to overcome the “reproducibility crisis” caused by the misuse of significance tests, this book provides a detailed explanation of the mechanism of p-hacking using significance tests, and concretely shows the merits of PHC as an alternative to p-values. In March 2019, two impactful papers on statistics were published. One paper, "Moving to a World Beyond ‘p 0.05’”, was featured in the scholarly journal emThe American Statistician/em, overseen by the American Statistical Association. The title of the first chapter is “Don't Say ‘Statistically Significant’”, and it uses the imperative form to clearly forbid the use of significance testing. Another paper, “Retire statistical significance”, was published in the prestigious scientific journal emNature/em. This commentary was endorsed by more than 800 scientists, advocating for the statement, “We agree, and call for the entire concept of statistical significance to be abandoned.” Consider a study comparing the duration of hospital stays between treatments A and B. Previously, research conclusions were typically stated as: “There was a statistically significant difference at the 5% level in the average duration of hospital stays.” This phrasing is quite abstract. Instead, we present the following conclusion as an example: (1) The average duration of hospital stays for Group A is at least half a day shorter than for Group B. (2) 71% of patients in Group A have shorter hospital stays than the average for Group B. (3) Group A has an average hospital stay that is, on average, no more than 94% of that of Group B. Then, the probability that the expression is correct is shown. That is the PHC curve.



Encyclopedia Of Biopharmaceutical Statistics Four Volume Set


Encyclopedia Of Biopharmaceutical Statistics Four Volume Set
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Author : Shein-Chung Chow
language : en
Publisher: CRC Press
Release Date : 2018-09-03

Encyclopedia Of Biopharmaceutical Statistics Four Volume Set written by Shein-Chung Chow and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Medical categories.


Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug development process, (2) gives a well-balanced summary of current regulatory requirements, and (3) describes recently developed statistical methods in the pharmaceutical sciences. Features of the Fourth Edition: 1. 78 new and revised entries have been added for a total of 308 chapters and a fourth volume has been added to encompass the increased number of chapters. 2. Revised and updated entries reflect changes and recent developments in regulatory requirements for the drug review/approval process and statistical designs and methodologies. 3. Additional topics include multiple-stage adaptive trial design in clinical research, translational medicine, design and analysis of biosimilar drug development, big data analytics, and real world evidence for clinical research and development. 4. A table of contents organized by stages of biopharmaceutical development provides easy access to relevant topics. About the Editor: Shein-Chung Chow, Ph.D. is currently an Associate Director, Office of Biostatistics, U.S. Food and Drug Administration (FDA). Dr. Chow is an Adjunct Professor at Duke University School of Medicine, as well as Adjunct Professor at Duke-NUS, Singapore and North Carolina State University. Dr. Chow is the Editor-in-Chief of the Journal of Biopharmaceutical Statistics and the Chapman & Hall/CRC Biostatistics Book Series and the author of 28 books and over 300 methodology papers. He was elected Fellow of the American Statistical Association in 1995.



Statistical Modelling And Regression Structures


Statistical Modelling And Regression Structures
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Author : Thomas Kneib
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-01-12

Statistical Modelling And Regression Structures written by Thomas Kneib and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-12 with Mathematics categories.


The contributions collected in this book have been written by well-known statisticians to acknowledge Ludwig Fahrmeir's far-reaching impact on Statistics as a science, while celebrating his 65th birthday. The contributions cover broad areas of contemporary statistical model building, including semiparametric and geoadditive regression, Bayesian inference in complex regression models, time series modelling, statistical regularization, graphical models and stochastic volatility models.



Bayesian Data Analysis Third Edition


Bayesian Data Analysis Third Edition
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Author : Andrew Gelman
language : en
Publisher: CRC Press
Release Date : 2013-11-01

Bayesian Data Analysis Third Edition written by Andrew Gelman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-01 with Mathematics categories.


Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.



Journal Of The American Statistical Association


Journal Of The American Statistical Association
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Author :
language : en
Publisher:
Release Date : 2008

Journal Of The American Statistical Association written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Statistics categories.




Bayesian Nonparametric Data Analysis


Bayesian Nonparametric Data Analysis
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Author : Peter Müller
language : en
Publisher: Springer
Release Date : 2015-06-17

Bayesian Nonparametric Data Analysis written by Peter Müller and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-17 with Mathematics categories.


This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.



Statistica Sinica


Statistica Sinica
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Author :
language : en
Publisher:
Release Date : 2004

Statistica Sinica written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Mathematical statistics categories.




Current Index To Statistics Applications Methods And Theory


Current Index To Statistics Applications Methods And Theory
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Author :
language : en
Publisher:
Release Date : 1991

Current Index To Statistics Applications Methods And Theory written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Mathematical statistics categories.


The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.