This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinical psychological scientists.
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Aidan Wright is Associate Professor of Psychology at the University of Pittsburgh, where he primarily teaches graduate statistics. His work has been recognized by several awards, including the Society for a Science of Clinical Psychology's Susan Nolen-Hoeksema Early Career Research Award and the American Psychologists' Association's David Shakow Early Career Award for Contributions to Clinical Psychology.
Michael Hallquist is Assistant Professor in the Department of Psychology at Pennsylvania State University. His research is supported by the National Institute of Mental Health and, in 2019, he received the Young Investigator Award from the International Society for the Study of Personality Disorders.
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Paperback. Etat : new. Paperback. This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinical psychological scientists. This Handbook provides an overview and guide for state-of-the-art research methods in clinical psychological science. It is the ideal resource for clinical psychologists, graduate students studying clinical psychology, and practitioners or researchers in allied disciplines including psychiatry and social work. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781316639528
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