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"Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets "--

Ecology --- Evolution --- Meta-analysis. --- Statistical methods. --- Mathematical models. --- Science --- Mathematics --- Life Sciences --- Ecology. --- Evolution. --- Probability & Statistics --- General. --- Meta-Analysis --- Statistical methods --- Mathematical models --- Ecology - Statistical methods --- Evolution - Mathematical models

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Cognitive neuroscientists increasingly claim that brain images generated by new brain imaging technologies reflect, correlate, or represent cognitive processes. This book warns against these claims, arguing that, despite its utility in anatomic and physiological applications, brain imaging research has not provided consistent evidence for correlation with cognition. It bases this argument on a review of the empirical literature, pointing to variability in data not only among subjects within individual experiments but also in the meta-analytical approach that pools data from different experiments.

Cognitive neuroscience. --- Cognitive neuropsychology --- Cognitive science --- Neuropsychology --- Meta-analysis. --- Brain --- Brain mapping. --- Brain mapping --- Cognition --- Physiology. --- Physiology --- COGNITIVE SCIENCES/Psychology/Cognitive Psychology --- NEUROSCIENCE/General --- COGNITIVE SCIENCES/General --- Psychology --- Connectome mapping --- Mapping of the brain --- Topographic brain mapping --- Cerebrum --- Mind --- Central nervous system --- Head --- Medicine --- Psychometrics --- Social sciences --- Localization of functions --- Research --- Evaluation --- Statistical methods --- 159.91 --- 159.95*1 --- 159.95*1 Cognitieve psychologie --- Cognitieve psychologie --- 159.91 Psychofysiologie. Neuropsychologie. Psychomotoriek. Psychomotorische therapie --- Psychofysiologie. Neuropsychologie. Psychomotoriek. Psychomotorische therapie

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This book presents an integrated methodology for sequential experimentation in clinical trials. The methodology allows sequential learning during the course of a trial to improve the efficiency of the trial design, which often lacks adequate information at the planning stage. Adaptation via sequential learning of unknown parameters is a central idea not only in adaptive designs of confirmatory clinical trials but also in the theory of optimal nonlinear experimental design, which the book covers as introductory material. Other introductory topics for which the book provides preparatory background include sequential testing theory, dynamic programming and stochastic optimization, survival analysis and resampling methods. In this way, the book gives a self-contained and thorough treatment of group sequential and adaptive designs, time-sequential trials with failure-time endpoints, and statistical inference at the conclusion of these trials. The book can be used for graduate courses in sequential analysis, clinical trials, and biostatistics, and also for short courses on clinical trials at professional meetings. Each chapter ends with supplements for the reader to explore related concepts and methods, and problems which can be used for exercises in graduate courses. Jay Bartroff is Associate Professor of Mathematics at the University of Southern California where he is a member of the Laboratory of Applied Pharmacokinetics at the USC Keck School of Medicine. He is a leading expert on group sequential and multistage adaptive statistical procedures and their applications to clinical trial designs, and he is a sought-after consultant in academia and industry. Tze Leung Lai is Professor of Statistics, and by courtesy, of Health Research and Policy and of the Institute of Computational and Mathematical Engineering at Stanford University, where he is the Director of the Financial and Risk Modeling Institute and Co-director of the Biostatistics Core at the Stanford Cancer Institute and of the Center for Innovative Study Design at the School of Medicine. He made seminal contributions to sequential analysis, innovative clinical trial designs, adaptive methods, survival analysis, nonlinear and generalized mixed models, hybrid resampling methods, and received the Committee of Presidents of Statistical Societies (COPSS) Award in 1983. Mei-Chiung Shih is Assistant Professor of Biostatistics and a member of the Stanford Cancer Institute and of the Center for Innovative Study Design at the School of Medicine at Stanford University. She is also Associate Director for Scientific and Technical Operations at the Department of Veterans Affairs (VA) Cooperative Studies Program Coordinating Center at Palo Alto Health Care System. She is a leading expert on group sequential and adaptive designs and inference of clinical trials, longitudinal and survival data analysis, and has been leading the design, conduct and analysis of several large trials at the VA.

Clinical trials -- Statistical methods. --- Clinical trials. --- Drugs -- Testing -- Statistical methods. --- Experimental design. --- Clinical trials --- Sequential analysis --- Epidemiologic Study Characteristics as Topic --- Health Care Evaluation Mechanisms --- Epidemiologic Methods --- Epidemiologic Research Design --- Investigative Techniques --- Models, Theoretical --- Research Design --- Mathematics --- Evaluation Studies as Topic --- Quality of Health Care --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Public Health --- Natural Science Disciplines --- Disciplines and Occupations --- Environment and Public Health --- Health Care Quality, Access, and Evaluation --- Health Care --- Models, Statistical --- Statistics as Topic --- Methods --- Clinical Trials as Topic --- Meta-Analysis as Topic --- Medicine --- Health & Biological Sciences --- Physical Sciences & Mathematics --- Medical Research --- Mathematical Statistics --- Statistical methods --- Statistical methods. --- Mathematical Sciences --- Applied Mathematics --- Statistics. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistics, general. --- Statistical Theory and Methods. --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Statistics .