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PDQ Statistics, Third Edition offers an expert overview of all major statistical methods, giving the reader a thorough understanding of statistics and how they are used in research articles. The book covers the major categories variable and descriptive statistics, parametric statistics, non-parametric statistics, and multivariate statistics. The explanations are clear, succinct, and loaded with practical examples. This third edition includes new chapters on hierarchical and logistic regression, path analysis, and structural equation modeling. PDQ Statistics, Third Edition also helps the reader identify those statistical analyses with basic flaws in design or research. The book s attractive design and humorous writing style make the subject matter accessible and engaging.
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"Using and Understanding Medical Statistics" Feature
Univ. of Waterloo, Canada. Presents many of the more complex statistical methods and techniques currently appearing in medical publications. This edition features new chapters on Poisson regression, the analysis of variance, meta-analysis, diagnostic tests, and more. For clinicians. Previous edition: c1996. Expanded-outline format. DNLM: Biometry-methods.
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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
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There has been substantial growth in the use of data monitoring committees in recent years, by both government agencies and the pharmaceutical industry. This growth has been brought about by increasing recognition of the value of such committees in safeguarding trial participants as well as protecting trial integrity and the validity of conclusions. This very timely book describes the operation of data monitoring committees, and provides an authoritative guide to their establishment, purpose and responsibilities. * Provides a practical overview of data monitoring in clinical trials. * Describes the purpose, responsibilities and operation of data monitoring committees. * Provides directly applicable advice for those managing and conducting clinical trials, and those serving on data monitoring committees. * Gives insight into clinical data monitoring to those sitting on regulatory and ethical committees. * Discusses issues pertinent to those working in clinical trials in both the US and Europe. The practical guidance provided by this book will be of use to professionals working in and/or managing clinical trials, in academic, government and industry settings, particularly medical statisticians, clinicians, trial co-ordinators, and those working in regulatory affairs and bioethics.
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Shop for Save Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics.Save and Options of Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics from variety stores in usa. 2013 Deal.
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Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics Description
Quantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community.
Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts.
The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and a clear distinction is made between a) knowledge and concepts that all students should ensure they understand and b) those that can be pursued by students who wish to do so.
The authors incorporate a program of practical exercises in SPSS using a prepared data set that helps to consolidate the theory and develop skills and confidence in data handling, analysis and interpretation.
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Statistics for Technology: A Course in Applied Statistics, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) Description
One of the most popular introductory texts in its field, Statistics for Technology: A Course in Applied Studies presents the range of statistical methods commonly used in science, social science, and engineering. The mathematics are simple and straightforward; statistical concepts are explained carefully; and real-life (rather than contrived) examples are used throughout the chapters. Divided into three parts, the Introduction describes some simple methods of summarizing data. Theory examines the basic concepts and theory of statistics. Applications covers the planning and procedures of experiments, quality control, and life testing. Revised throughout, this Third Edition places a higher priority on the role of computers in analysis, and many new references have been incorporated. A new appendix describes general methods of tackling statistical problems, including guidance on literature searching and report writing.
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Inferential statistical methods as applied to medical research, presented in a progressive manner with examples and answers covering topics such as probability, means, proportions, regression and correlation, and nonparametric methods.
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Practical Statistics for Medical Research (Chapman & Hall/CRC Texts in Statistical Science)
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Most medical researchers, whether clinical or non-clinical, receive some background in statistics as undergraduates. However, it is most often brief, a long time ago, and largely forgotten by the time it is needed. Furthermore, many introductory texts fall short of adequately explaining the underlying concepts of statistics, and often are divorced from the reality of conducting and assessing medical research.
Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background.
The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.
Selection Bias and Covariate Imbalances in Randomized Clinical Trials (Statistics in Practice) by Wiley
Selection bias can, and does, occur, even in randomized clinical trials. Steps need to be taken in order to ensure that this does not compromise the integrity of clinical trials; hence “Selection Bias and Covariate Imbalances in Randomized Clinical Trials" offers a comprehensive treatment of the subject and the methodology involved. This book:
Provides an overview of the hierarchy of study designs, and justifies the position of randomised trials at the top of this hierarchy.
Discusses the strengths and defects of randomisation, and provides real evidence to justify concern regarding its defects.
Outlays the damaging consequences that selection bias causes when it does occur.
Considers courses of action that can be taken to manage/ contain the problem.
Presents methods that can be used to detect selection bias in randomised trials, and methods to correct for selection bias.
Concludes by providing a comprehensive plan for managing baseline imbalances and selection bias in randomised trials, and proposing open problems for future research.
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.
Nonparametric Statistics for Health Care Research: Statistics for Small Samples and Unusual Distributions by SAGE Publications, Inc
This book will help the reader select and interpret the most appropriate statistical tests to enable the effective assessment of a particular intervention. Beginning with a general overview of nonparametric statistics, Majorie A Pett reviews statistical hypothesis testing and the characteristics of data. She then explores "goodness of fit" tests, tests for two related samples, repeated measures for multiple time periods or matched conditions, tests for two independent samples, tests to assess differences among independent groups and tests for association between variables.
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Written for people who want to learn or brush-up on the basics of statistics but question their abilities, this book offers a step-by-step introduction to the topic. The book begins with an introduction to the language of statistics and then covers descriptive statistics and inferential statistics. Throughout, the author offers readers:
- Difficulty Rating Index for each chapter's material
- Tips for doing and thinking about a statistical technique
- Top tens for everything from the best ways to create a graph to the most effective techniques for data collection
- Steps that break techniques down into a clear sequence of procedures
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- Practice exercises at the end of each chapter, followed by worked out solutions.
The book concludes with a statistical software sampler and a description of the best Internet sites for statistical information and data resources. Readers also have access to a website for downloading data that they can use to practice additional exercises from the book. Students and researchers will appreciate the book’s unhurried pace and thorough, friendly presentation.
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Save Product Available. Save How to Report Statistics in Medicine: Annotated Guidelines for Authors, Editors, and Reviewers. Compare your Save price with best online store. Choose your best product Shopping online.
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Main Features : How to Report Statistics in Medicine: Annotated Guidelines for Authors, Editors, and Reviewers
How to Report Statistics in Medicine presents a comprehensive and comprehensible set of guidelines for reporting the statistical analyses and research designs and activities commonly used in biomedical research. Containing elements of a reference book, a style manual, a dictionary, an encyclopedia, and a text book, it is the standard guide in the fields of medical writing, scientific publications, and evidence-based medicine throughout the world. Features: Specific, detailed guidelines for reporting and interpreting statistics and research designs and activities in biomedical science. Sample presentations that guide you in reporting statistics correctly and completely. Coverage of current and emerging topics in statistics and trial design. Written by a senior medical writer and a senior biostatistician, the text is both clear and accurate, and the information is complete and pragmatic. Designed for anyone who needs to interpret or report statistics in medicine.
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Main Features : Medical Statistics from Scratch: An Introduction for Health Professionals (Bowers, Medical Statistics from Scratch: An Introduction for)
This long awaited second edition of this bestseller continues to provide a comprehensive, user friendly, down-to-earth guide to elementary statistics. The book presents a detailed account of the most important procedures for the analysis of data, from the calculation of simple proportions, to a variety of statistical tests, and the use of regression models for modeling of clinical outcomes.
The level of mathematics is kept to a minimum to make the material easily accessible to the novice, and a multitude of illustrative cases are included in every chapter, drawn from the current research literature. The new edition has been completely revised and updated and includes new chapters on basic quantitative methods, measuring survival, measurement scales, diagnostic testing, bayesian methods, meta-analysis and systematic reviews.
"... After years of trying and failing, this is the only book on statistics that i have managed to read and understand" - Naveed Kirmani, Surgical Registrar, South London Healthcare HHS Trust, UK
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Product Name : Applied Mixed Models in Medicine (Statistics in Practice)
A mixed model allows the incorporation of both fixed and random variables within a statistical analysis. This enables efficient inferences and more information to be gained from the data. The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry. There have been many recent advances in mixed modelling, particularly regarding the software and applications. This new edition of a groundbreaking text discusses the latest developments, from updated SAS techniques to the increasingly wide range of applications.
Presents an overview of the theory and applications of mixed models in medical research, including the latest developments and new sections on bioequivalence, cluster randomised trials and missing data.
Easily accessible to practitioners in any area where mixed models are used, including medical statisticians and economists.
Includes numerous examples using real data from medical and health research, and epidemiology, illustrated with SAS code and output.
Features new version of SAS, including the procedure PROC GLIMMIX and an introduction to other available software.
Supported by a website featuring computer code, data sets, and further material, available at: http://www.chs.med.ed.ac.uk/phs/mixed/.
This much-anticipated second edition is ideal for applied statisticians working in medical research and the pharmaceutical industry, as well as teachers and students of statistics courses in mixed models. The text will also be of great value to a broad range of scientists, particularly those working the medical and pharmaceutical areas.
Product Description : Applied Mixed Models in Medicine (Statistics in Practice)
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Save Price Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence (Wiley Series in Probability and Statistics)
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Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments. The authors aim to promote a deeper understanding of the notion of statistical evidence.
The book is comprised of two parts – The Handbook, and The Theory. The Handbook is a guide for combining and interpreting experimental evidence to solve standard statistical problems. This section allows someone with a rudimentary knowledge in general statistics to apply the methods. The Theory provides the motivation, theory and results of simulation experiments to justify the methodology.
This is a coherent introduction to the statistical concepts required to understand the authors’ thesis that evidence in a test statistic can often be calibrated when transformed to the right scale.
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