Publisher's Synopsis
From the preface
The "threshold p-value"-the arbiter of statistical significance-has been a widely used gateway to believability and acceptance for publication in scientific research since 1925. However, a growing number of statisticians and other researchers say we should "move beyond" these ideas, suggesting we should greatly reduce our emphasis on them in scientific research. These authors are waging a well-intentioned, polite, and vigorous intellectual war on the ideas of a threshold p-value and statistical significance. This is a "good" war, because it forces important issues into the open, where they can be best understood and assessed.
This book grew from a sense that the threshold-p-value gateway to publication of scientific research results is highly useful but is also widely misunderstood. The book presents, from first principles, a modern view of the role of the gateway, as used by some scientific journals. The ideas are explained in terms of the recent disagreement about them between the editorial in a Special Issue on Statistical Inference of the American Statistician and a subsequent editorial in the New England Journal of Medicine.
The ideas are developed with almost no reference to mathematics. (A computer can do all the standard math if the user properly understands the key ideas.) The explanations are reinforced with practical examples. The discussion shows how the concept of a threshold-p-value gateway helps researchers and journal editors maximize the overall scientific, social, and commercial benefit of scientific research. The gateway does this by optimally balancing the rates of costly "false-positive" and "false-negative" errors in a scientific journal.
The book also discusses the important related ideas of a relationship between variables, a scientific hypothesis test, and the "replication crisis" in some branches of scientific research.
The body of the book, which covers the key ideas, is roughly 30% of the text. The remainder consists of 23 appendices that expand the ideas in useful directions.
The material is aimed at scientific researchers, journal editors, science teachers, and science students in the biological, social, and physical sciences. It will also be of interest to statisticians, data scientists, philosophers of science, and lay readers seeking an integrated modern view of the high-level operation of the study of relationships between variables in scientific research.
About the author
Donald B. Macnaughton has been a statistical consultant for more than 40 years. He has managed the statistical aspects of research in the fields of experimental psychology, zoology, drug dependence, nursing, education, business, geography, physical education, and inmate rehabilitation, among others. His consulting work supports and informs his main interest, which is to read, understand, and write about the vital role of the field of statistics in scientific research.
