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This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians, and they focus on the mathematical background. These books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the application of multilevel analysis in research. It addresses the practical issues that confront those undertaking research and wanting to find the correct answers to research questions. This book is written for non-mathematical researchers and it explains when and how to use multilevel analysis. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyse the data. This approach will help to bridge the conceptual and communication gap that exists between those undertaking research and statisticians.
Biomathematics. Biometry. Biostatistics --- Mathematical statistics --- Model, Statistical --- Models, Binomial --- Models, Polynomial --- Statistical Model --- Probabilistic Models --- Statistical Models --- Two-Parameter Models --- Binomial Model --- Binomial Models --- Model, Binomial --- Model, Polynomial --- Model, Probabilistic --- Model, Two-Parameter --- Models, Probabilistic --- Models, Two-Parameter --- Polynomial Model --- Polynomial Models --- Probabilistic Model --- Two Parameter Models --- Two-Parameter Model --- Analysis of variance --- Medical statistics --- Medicine --- Biomedical Research --- Models, Statistical --- Multivariate Analysis --- Statistics as Topic --- multivariaat --- regressie-analyse --- wiskundige statistiek --- Analyses, Multivariate --- Analysis, Multivariate --- Multivariate Analyses --- Biomedical research --- Medical research --- Health --- Health statistics --- Statistics --- ANOVA (Analysis of variance) --- Variance analysis --- Experimental design --- Research --- methods --- Statistical methods --- Models, Statistical. --- Multivariate Analysis. --- Analysis of variance. --- Medical statistics. --- methods. --- Research. --- Health Workforce --- Canonical Correlation --- Canonical Correlations --- Correlation, Canonical --- Health Sciences --- General and Others
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The fourth edition of Risk Adjustment for Measuring Health Care Outcomes presents the fundamental principles and concepts of risk adjustment for comparing outcomes of care and explains why risk adjustment is a critical tool for measuring quality and setting reimbursement rates. This book is a comprehensive guide to the issues raised by risk adjustment, including the pros and cons of different data sources, the validity and reliability of risk adjustment methods, the effects of various statistical modeling approaches, and concerns relating to special populations.The fourth edition features:A new chapter on the role of risk adjustment in managing healthcare organizations New information on risk factors, including genetics and social and environmental determinants of health Perspectives on electronic health records and new health information technologies Explanations of new statistical methods for comparing provider outcomes and their implications for risk adjustmentInstructor Resources: Discussion questions and PowerPoint slides of the book exhibits. To see a sample, click on the Instructor Resource sample tab above.
Outcome Assessment, Health Care --- Risk Adjustment --- Decision Support Techniques. --- Delivery of Health Care --- Models, Statistical. --- Risk Factors. --- Population at Risk --- Populations at Risk --- Health Correlates --- Risk Factor Scores --- Risk Scores --- Correlates, Health --- Factor, Risk --- Risk Factor --- Risk Factor Score --- Risk Score --- Score, Risk --- Score, Risk Factor --- Organs at Risk --- Model, Statistical --- Models, Binomial --- Models, Polynomial --- Statistical Model --- Probabilistic Models --- Statistical Models --- Two-Parameter Models --- Binomial Model --- Binomial Models --- Model, Binomial --- Model, Polynomial --- Model, Probabilistic --- Model, Two-Parameter --- Models, Probabilistic --- Models, Two-Parameter --- Polynomial Model --- Polynomial Models --- Probabilistic Model --- Two Parameter Models --- Two-Parameter Model --- Statistics as Topic --- Analysis, Decision --- Decision Aids --- Decision Support Technics --- Decision Analysis --- Decision Modeling --- Models, Decision Support --- Aid, Decision --- Aids, Decision --- Analyses, Decision --- Decision Aid --- Decision Analyses --- Decision Support Model --- Decision Support Models --- Decision Support Technic --- Decision Support Technique --- Model, Decision Support --- Modeling, Decision --- Technic, Decision Support --- Technics, Decision Support --- Technique, Decision Support --- Techniques, Decision Support --- Clinical Decision-Making --- Decision Making --- Decision Making, Organizational --- methods. --- organization & administration. --- United States. --- Social Risk Factors --- Factor, Social Risk --- Factors, Social Risk --- Risk Factor, Social --- Risk Factors, Social --- Social Risk Factor --- Decision Support Techniques --- Models, Statistical --- Outcome Assessment (Health Care) --- Risk Factors --- W 84 Health services. Quality of health care (General)
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