Towards A New Paradigm For Statistical Evidence
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Towards a New Paradigm for Statistical Evidence
Many scientists now widely agree that the current paradigm of statistical significance should be abandoned or largely modified. In response to these calls for change, a Special Issue of Econometrics (MDPI) has been proposed. This book is a collection of the articles that have been published in this Special Issue. These seven articles add new insights to the problem and propose new methods that lay a solid foundation for the new paradigm for statistical significance.
Towards a New Paradigm for Statistical Evidence
Many scientists now widely agree that the current paradigm of statistical significance should be abandoned or largely modified. In response to these calls for change, a Special Issue of Econometrics (MDPI) has been proposed. This book is a collection of the articles that have been published in this Special Issue. These seven articles add new insights to the problem and propose new methods that lay a solid foundation for the new paradigm for statistical significance.
Causality, Probability, and Medicine
Why is understanding causation so important in philosophy and the sciences? Should causation be defined in terms of probability? Whilst causation plays a major role in theories and concepts of medicine, little attempt has been made to connect causation and probability with medicine itself. Causality, Probability, and Medicine is one of the first books to apply philosophical reasoning about causality to important topics and debates in medicine. Donald Gillies provides a thorough introduction to and assessment of competing theories of causality in philosophy, including action-related theories, causality and mechanisms, and causality and probability. Throughout the book he applies them to important discoveries and theories within medicine, such as germ theory; tuberculosis and cholera; smoking and heart disease; the first ever randomized controlled trial designed to test the treatment of tuberculosis; the growing area of philosophy of evidence-based medicine; and philosophy of epidemiology. This book will be of great interest to students and researchers in philosophy of science and philosophy of medicine, as well as those working in medicine, nursing and related health disciplines where a working knowledge of causality and probability is required.