Charles S. Reichardt – författare

This book illustrates the method of multiple hypotheses with detailed examples and describes the limitations facing all methods (including the method of multiple hypotheses) as the means for constructing knowledge about nature. Author Charles Reichardt explains the method of multiple hypotheses using a range of real-world applications involving the causes of crime, traffic fatalities, and home field advantage in sports. The book describes the benefits of utilizing multiple hypotheses and the inherent limitations within which all methods must operate because all conclusions about nature must remain tentative and forever subject to revision. Nonetheless, the book reveals how the method of multiple hypotheses can produce strong inferences even in the face of the inevitable uncertainties of knowledge. The author also explicates some of the most foundational ideas in philosophy of science including the notions of the underdetermination of theory by data, the Duhem-Quine thesis, and the theory-ladenness of observation.This book will be important reading for advanced undergraduates, graduates, and professional researchers across the social, behavioral, and natural sciences wanting to understand this method and how to apply it to their field of interest.

This book illustrates the method of multiple hypotheses with detailed examples and describes the limitations facing all methods (including the method of multiple hypotheses) as the means for constructing knowledge about nature. Author Charles Reichardt explains the method of multiple hypotheses using a range of real-world applications involving the causes of crime, traffic fatalities, and home field advantage in sports. The book describes the benefits of utilizing multiple hypotheses and the inherent limitations within which all methods must operate because all conclusions about nature must remain tentative and forever subject to revision. Nonetheless, the book reveals how the method of multiple hypotheses can produce strong inferences even in the face of the inevitable uncertainties of knowledge. The author also explicates some of the most foundational ideas in philosophy of science including the notions of the underdetermination of theory by data, the Duhem-Quine thesis, and the theory-ladenness of observation.This book will be important reading for advanced undergraduates, graduates, and professional researchers across the social, behavioral, and natural sciences wanting to understand this method and how to apply it to their field of interest.

Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest–posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Comparing quasi-experiments to randomized experiments, Reichardt discusses when and why the former might be a better choice than the latter in the face of the contingencies that are likely to arise in practice. Modern methods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility. Adding to its discussion of prototypical quasi-experiments, the book also provides a complete typology of quasi-experimental design options to help the reader craft the best research design to fit the circumstances of a given study.