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This book examines Stata's treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are "mixed" because they allow fixed and random effects, and they are "generalized" because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables. Volume I covers continuous Gaussian linear mixed models and has nine chapters. The chapters are organized in four parts. Volume II discusses generalized linear mixed models for binary, categorical, count, and survival outcomes.
Volume I is devoted to continuous Gaussian linear mixed models and has nine chapters. The chapters are organized in four parts. The first part provides a review of the methods of linear regression. The second part provides an in-depth coverage of the two-level models, the simplest extensions of a linear regression model. The mixed-model foundation and the in-depth coverage of the mixed-model principles provided in volume I for continuous outcomes, make it straightforward to transition to generalized linear mixed models for noncontinuous outcomes described in volume II.
Experience Sampling in Mental Health Research provides comprehensive and user-friendly guidance on when and how to apply this methodology in the assessment of clinical populations. Divided into three sections, the book offers step-by-step instruction on how to design, develop and implement an ESM study, as well as advice on how this approach might be adapted for common mental health difficulties. With an eye to the future of this type of research, the contributors also consider how ESM might be adapted for use as a form of clinical assessment and intervention. Experience Sampling in Mental Health Research combines the knowledge and expertise of leading international experts in the field, and will be helpful for students, researchers and clinicians wishing to start or develop their understanding of this methodology.
This invaluable, jargon-free guide to essential medical terminology in an accessible A-Z format is ideal for medical, allied health and biomedical science students and researchers, clinicians and health care practitioners. Avoiding the complex language that is so often a feature of statistics and research methodology, this text provides clear and succinct explanations, clarifying meaning and showing the interdependencies between important concepts. This edition includes enhanced explanations of statistical concepts and methods—including more illustrative content—for greater accessibility. The book makes frequent use of examples from the medical literature, with reference to landmark studies, ensuring clinical relevance. It remains an ideal aid to accompany the reading and critical appraisal of medical and health care literature, now widely recognized to be a practical lifelong skill required by all health professionals throughout undergraduate and postgraduate studies and during clinical practice.
During the early development and throughout the short history of green/conservation criminology, limited attention has been directed toward quantitative analyses of relevant environmental crime, law and justice concerns. While recognizing the importance of establishing a theory and terminology in the early stages of development, this book redresses this imbalance. The work features contributions that undertake empirical quantitative studies of green/conservation crime and justice issues by both conservation and green criminologists. The collection highlights the shared concerns of these groups within important forms of ecological crime and victimization, and illustrates the ways in which these approaches can be undertaken quantitatively. It includes quantitative conservation/green criminological studies that represent the work of both well-established scholars in these fields, along with studies by scholars whose works are less well-known and who are also contributing to shaping this area of research. The book presents a valuable contribution to the areas of Green and Conservation Criminology. It will appeal to academics and students working in these areas.
Drawing on the work of 75 internationally acclaimed experts in the field, Handbook of Item Response Theory, Three-Volume Set presents all major item response models, classical and modern statistical tools used in item response theory (IRT), and major areas of applications of IRT in educational and psychological testing, medical diagnosis of patient-reported outcomes, and marketing research. It also covers CRAN packages, WinBUGS, Bilog MG, Multilog, Parscale, IRTPRO, Mplus, GLLAMM, Latent Gold, and numerous other software tools. A full update of editor Wim J. van der Linden and Ronald K. Hambleton’s classic Handbook of Modern Item Response Theory, this handbook has been expanded from 28 chapters to 85 chapters in three volumes. The three volumes are thoroughly edited and cross-referenced, with uniform notation, format, and pedagogical principles across all chapters. Each chapter is self-contained and deals with the latest developments in IRT.
Drawing on the work of internationally acclaimed experts in the field, Handbook of Item Response Theory, Volume 3: Applications presents applications of item response theory to practical testing problems. While item response theory may be known primarily for its advances in theoretical modeling of responses to test items, equal progress has been made in its providing innovative solutions to daily testing problems. This third volume in a three-volume set highlights the major applications. Specifically, this volume covers applications to test item calibration, item analysis, model fit checking, test-score interpretation, optimal test design, adaptive testing, standard setting, and forensic analyses of response data. It describes advances in testing in areas such as large-scale educational assessment, psychological testing, health measurement, and measurement of change. In addition, it extensively reviews computer programs available to run any of the models and applications in Volume One and Three. Features Includes contributions from internationally acclaimed experts with a history of advancing applications of item response theory Provides extensive cross-referencing and common notation across all chapters in this three-volume set Underscores the importance of treating each application in a statistically rigorous way Reviews major computer programs for item response theory analyses and applications. Wim J. van der Linden is a distinguished scientist and director of research and innovation at Pacific Metrics Corporation. Dr. van der Linden is also a professor emeritus of measurement and data analysis at the University of Twente. His research interests include test theory, adaptive testing, optimal test assembly, parameter linking, test equating, and response-time modeling as well as decision theory and its applications to problems of educational decision making.

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