Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology) by Cambridge University Press
This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians; those books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the practical application of multilevel analysis in research. 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 reanalyze the data. This approach will help bridge the conceptual and communication gap that exists between researchers and statisticians.Read more Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology)
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Main Features : Analysis of Variance (Quantitative Applications in the Social Sciences)
The second edition of this book provides a conceptual understanding of analysis of variance. It outlines methods for analysing variance that are used to study the effect of one or more nominal variables on a dependent, interval level variable. The book presumes only elementary background in significance testing and data analysis.
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Design and Analysis of Group- Randomized Trials Description
This text provides the most comprehensive treatment of the design and analytic issues involved in group-randomized trials. GRTs are comparative studies conducted to evaluate the effect of a health promotion intervention in which the units of assignment are identifiable groups (e.g., schools, worksites) and the units of observation are members of those groups (e.g., students, workers). The book reviews the underlying issues, the most widely used research designs, and analytic strategies. There is an emphasis on mixed-model regression, with two chapters illustrating the analytic methods in SAS PROC MIXED and GLIMMIX. There is also a detailed chapter on power analysis and sample size calculation.
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Main Features : Introduction to Meta-Analysis (Statistics in Practice)
This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Introduction to Meta-Analysis:
Outlines the role of meta-analysis in the research process
Shows how to compute effects sizes and treatment effects
Explains the fixed-effect and random-effects models for synthesizing data
Demonstrates how to assess and interpret variation in effect size across studies
Clarifies concepts using text and figures, followed by formulas and examples
Explains how to avoid common mistakes in meta-analysis
Discusses controversies in meta-analysis
Features a web site with additional material and exercises
A superb combination of lucid prose and informative graphics, written by four of the world’sleading experts on all aspects of meta-analysis. Borenstein, Hedges, Higgins, and Rothsteinprovide a refreshing departure from cookbook approaches with their clear explanations ofthe what and why of meta-analysis. The book is ideal as a course textbook or for self-study.My students, who used pre-publication versions of some of the chapters, raved about theclarity of the explanations and examples. David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics.
The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual,and it is amazingly successful at achieving that goal. The reader can comfortably skip theformulas and still understand their application and underlying motivation. For the morestatistically sophisticated reader, the relevant formulas and worked examples provide a superbpractical guide to performing a meta-analysis. The book provides an eclectic mix of examplesfrom education, social science, biomedical studies, and even ecology. For anyone consideringleading a course in meta-analysis, or pursuing self-directed study, Introduction toMeta-analysis would be a clear first choice. Jesse A. Berlin, ScD
Introduction to Meta-Analysis is an excellent resource for novices and experts alike. The bookprovides a clear and comprehensive presentation of all basic and most advanced approachesto meta-analysis. This book will be referenced for decades. Michael A. McDaniel, Professor of Human Resources and Organizational Behavior, Virginia Commonwealth University
Buy Statistical Analysis of Medical Data: New Developments
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Written at a level suitable for graduate students working in medical statistics, this collection highlights four areas of active research: survival analysis, longitudinal data analysis, Bayesian methods, and imaging. Each article has been commissioned from leaders in the fields, and the collection reflects the rapid growth and wide application of statistical methods in medicine. Equally valuable for students and researchers, the book provides a practical introduction to current methods.
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Save Product Available. Save Clinical Trials - A Practical Guide to Design, Analysis, and Reporting. Compare your Save price with best online store. Choose your best product Shopping online.
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Main Features : Clinical Trials - A Practical Guide to Design, Analysis, and Reporting
This book is a friendly jargon buster, which aims to demystify clinical trials. It is divided into five sections: fundamentals of trial design, alternative trial designs, basics of statistical analysis, special trial issues in data analysis, and reporting of trials. Using simple language the book explains with illustrations of numerous trial examples, the conceptual and methodological issues that occur at all stages of clinical trial covering trial design, conduct, analysis and reporting. The book is an educational and approachable reference in a difficult area of medicine where clinicians often feel uncertain and this material helps them review, appraise and publish trials and clinical evidence. The audience for the book includes physicians, statisticians, pharmacists, medical students, clinical researchers, medical writers, data managers, study co-ordinators, pharmaceutical sales representatives, and financial (medical) analysts.
Meta-Analysis in Medicine and Health Policy (Chapman & Hall/CRC Biostatistics Series) by CRC Press
This remarkable text raises the analysis of data in health sciences and policy to new heights of refinement and applicability by introducing cutting-edge meta-analysis strategies while reviewing more commonly used techniques. Each chapter builds on sound principles, develops methodologies to solve statistical problems, and presents concrete applications used by experienced medical practitioners and health policymakers. Written by more than 30 celebrated international experts, Meta-Analysis in Medicine and Health Policy employs copious examples and pictorial presentations to teach and reinforce biostatistical techniques more effectively and poses numerous open questions of medical and health policy research.Read more Meta-Analysis in Medicine and Health Policy (Chapman & Hall/CRC Biostatistics Series)
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Buy Design and Analysis of Cluster Randomization Trials in Health Research
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A cluster randomization trial is one in which intact social units, or clusters of individuals, are randomized to different intervention groups. Trials randomizing clusters have become particularly widespread in the evaluation of non-therapeutic interventions, including lifestyle modification, educational programmes and innovations in the provision of health care. The increasing popularity of this design among health researchers over the past two decades has led to an extensive body of methodology on the subject. This is the first book to present a systematic and united treatment of this topic; it contains distinctive chapters on the history of cluster randomized trials, ethical issues and reporting guidelines.
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Twin and family data have traditionally been used to quantify the genetic and environmental contribution to disease. Through the application of new analytical approaches, these designs can also provide powerful models in which the search for specific genes underlying non-Mendelian diseases can be optimised. This book discusses the state-of-the-art in twin and sib-pairs analysis of complex diseases both from the perspective of epidemiology (study design, subject selection, sampling strategies) and biostatistics (path analysis, survival analysis, linkage analysis, association studies). Novel ways are discussed in which twins and sib-pairs can be used to meet the challenge of identifying the location and function of genes underlying complex traits. This book will appeal to a wide range of biomedical scientists interested in the genetic basis of disease, epidemiologists, molecular biologists, human geneticists and students.
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Medical Statistics: A Guide to Data Analysis and Critical Appraisal
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Holistic approach to understanding medical statistics
This hands-on guide is much more than a basic medical statistics introduction. It equips you with the statistical tools required for evidence-based clinical research.
Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs.
Showing you how to:
analyse data with the help of data set examples (Click here to download datasets)
select the correct statistics and report results for publication or presentation
understand and critically appraise results reported in the literature
Each statistical test is linked to the research question and the type of study design used. There are also checklists for critically appraising the literature and web links to useful internet sites.
Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors’ popular medical statistics courses. Critical appraisal guidelines at the end of each chapter help the reader evaluate the statistical data in their particular contexts.
Review Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research
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Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research presents a straightforward explanation of the complex statistical procedures involved in factor analysis. Authors Marjorie A. Pett, Nancy M. Lackey, and John J. Sullivan provide a step-by-step approach to analyzing data using statistical computer packages like SPSS and SAS. Emphasizing the interrelationship between factor analysis and test construction, the authors examine numerous practical and theoretical decisions that must be made to efficiently run and accurately interpret the outcomes of these sophisticated computer programs.
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Buy Systematic Reviews in Health Care: Meta-Analysis in Context
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The second edition of this best-selling book has been thoroughly revised and expanded to reflect the significant changes and advances made in systematic reviewing. New features include discussion on the rationale, meta-analyses of prognostic and diagnostic studies and software, and the use of systematic reviews in practice.
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Buy Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets and DEA Excel Solver (International ... Research and Management Science, 51)
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This book introduces DEA as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective. This book also provides easy-to-use DEA software - DEA Excel Solver. This DEA Excel Solver is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches, which include more than 150 different DEA models. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational efficiency issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, e-business, public services and many other industries. The DEA Excel Solver does not set limit on the number of units, inputs or outputs. With the capacity of Excel Solver, the DEA Excel Solver can deal with large sized performance evaluation tasks. For a free version of DEA Excel Solver, please visit www.deafrontier.com.
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Save Price Design and Analysis of Clinical Experiments (Wiley Classics Library)
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The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T.W. Anderson The Statistical Analysis of Time Series T.S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I Richard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research Amos de Shalit & Herman Feshbach Theoretical Nuclear Physics, Volume 1—Nuclear Structure Harold F. Dodge & Harry G. Romig Sampling Inspection Tables: Single and Double Sampling J. L. Doob Stochastic Processes Nelson Dunford & Jacob T. Schwartz Linear Operators, Part One, General Theory Nelson Dunford & Jacob T. Schwartz Linear Operators, Part Two, Spectral Theory—Self Adjoint Operators in Hilbert Space Nelson Dunford & Jacob T. Schwartz Linear Operators, Part Three, Spectral Operators Regina C. Elandt-Johnson & Norman L. Johnson Survival Models and Data Analysis Herman Feshbach Theoretical Nuclear Physics: Nuclear Reactions Joseph L. Fleiss Design and Analysis of Clinical Experiments Bernard Friedman Lectures on Applications-Oriented Mathematics Phillip Griffiths & Joseph Harris Principles of Algebraic Geometry Gerald J. Hahn & Samuel S. Shapiro Statistical Models in Engineering Marshall Hall, Jr. Combinatorial Theory, Second Edition Morris H. Hansen, William N. Hurwitz & William G. Madow Sample Survey Methods and Theory, Volume I—Methods and Applications Morris H. Hansen, William N. Hurwitz & William G. Madow Sample Survey Methods and Theory, Volume II—Theory Peter Henrici Applied and Computational Complex Analysis, Volume 1—Power Series—Integration—Conformal Mapping—Location of Zeros Peter Henrici Applied and Computational Complex Analysis, Volume 2—Special Functions—Integral Transforms—Asymptotics—Continued Fractions Peter Henrici Applied and Computational Complex Analysis, Volume 3—Discrete Fourier Analysis— Cauchy Integrals—Construction of Conformal Maps—Univalent Functions Peter Hilton & Yel-Chiang Wu A Course in Modern Algebra Harry Hochstadt Integral Equations Leslie Kish Survey Sampling Shoshichi Kobayashi & Katsumi Nomizu Foundations of Differential Geometry, Volume I Shoshichi Kobayashi & Katsumi Nomizu Foundations of Differential Geometry, Volume 2 Erwin O. Kreyszig Introductory Functional Analysis with Applications William H. Louisell Quantum Statistical Properties of Radiation Rupert G. Miller Jr. Survival Analysis Ali Hasan Nayfeh Introduction to Perturbation Techniques Ali Hasan Nayfeh & Dean T. Mook Nonlinear Oscillations Emanuel Parzen Modern Probability Theory & Its Applications P. M. Prenter Splines and Variational Methods Walter Rudin Fourier Analysis on Groups Lawrence S. Schulman Techniques and Applications of Path Integration Shayle R. Searle Linear Models I. H. Segel Enzyme Kinetics: Behavior and Analysis of Rapid Equilibrium and Steady-State Enzyme Systems C. L. Siegel Topics in Complex Function Theory, Volume I—Elliptic Functions and Uniformization Theory C. L. Siegel Topics in Complex Function Theory, Volume II—Automorphic and Abelian Integrals C. L. Siegel Topics in Complex Function Theory, Volume III—Abelian Functions and Modular Functions of Several Variables L. Spitzer Physical Processes in the Interstellar Medium J. J. Stoker Differential Geometry J. J. Stoker Water Waves: The Mathematical Theory with Applications J. J. Stoker Nonlinear Vibrations in Mechanical and Electrical Systems Richard Zallen The Physics of Amorphous Solids Arnold Zellner Introduction to Bayesian Inference in Econometrics
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Power Analysis for Experimental Research: A Practical Guide for the Biological, Medical and Social Sciences by Cambridge University Press
Power analysis is an essential tool for determining whether a statistically significant result can be expected in a scientific experiment prior to the experiment being performed. This comprehensive, accessible book provides practicing researchers with step-by-step instructions for conducting power/sample size analyses, assuming only basic prior knowledge of summary statistics and normal distribution. It contains a unified approach to statistical power analysis, with numerous easy-to-use tables that make further calculations or statistical expertise unnecessary.Read more Power Analysis for Experimental Research: A Practical Guide for the Biological, Medical and Social Sciences
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Save Price Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis
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Evaluating the strength or persuasiveness of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. There are a myriad of potential biases to consider, but little guidance about how to asses the likely impact on study results. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of epidemiologic research in order to better evaluate it successes and limitations. The focus throughout is on practical tools for making optimal use of available data to assess whether hypothesized biases are operative and to anticipate concerns at the point of study design in order to ensure that needed information is generated. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated. The potential value of each approach as well as its limitations are discussed, using examples from the published literature. Such information should help those who generate and interpret epidemiologic research to apply methodological principles more effectively to substantive issues, leading to a more accurate appraisal of the current evidence and greater clarity about research needs.
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