Best Applied Multilevel Analysis: A Practical Guide for Medical Researchers (Practical Guides to Biostatistics and Epidemiology)

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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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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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.

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Buy Qualitative Methods in Public Health: A Field Guide for Applied Research

Qualitative Methods in Public Health: A Field Guide for Applied Research by Jossey-Bass




Qualitative Methods in Public Health is a comprehensive resource that presents practical strategies and methods for using qualitative research and includes the basic logic and rationale for making qualitative research decisions. This important book outlines the complexities, advantages, and limitations of qualitative methods and offers information and step-by-step procedures for every phase of research¾from theory to study design, data collection, analysis, interpretation, writing, and dissemination. Written for faculty, students, and practitioners in public health research, promotion, and education Qualitative Methods in Public Health will help those with prior research experience expand their repertoire to include qualitative methods.  The book also contains up-to-date illustrations from a  wealth of topics such as reproductive choice, sexual risk and protection, gender relations, and other areas critical to understanding population, health, and disease. Qualitative Methods in Public Health includes 

• Examples of mixed qualitative-quantitative research design
• Guidelines for discussions, sample budgets, and caveats for planning and implementing focus groups
• Sample agenda for training interviewers 
• A summary of needed critical appraisal skills
• Tips on where to publish the results
• Sample brochure to share qualitative study findings with participating communities
• A comprehensive index

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Single-case research has played an important role in developing and evaluating interventions that are designed to alter a particular facet of human functioning. Now thoroughly updated in its second edition, acclaimed author Alan E. Kazdin's Single-Case Research Designs provides a notable contrast to the quantitative methodology approach that pervades the biological and social sciences. While focusing on widely applicable methodologies for evaluating interventions--such as treatment or psychotherapy using applied behavior analysis--this revised edition also encompasses a broader range of research areas that utilize single-case designs, demonstrating the pertinence of this methodology in various disciplines, from psychology and medicine to business and industry.

This well-written, clear, and thoroughly updated text is ideal for practitioners, instructors, and students alike.

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Applied Quantitative Methods for Health Services Management

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University of New Hampshire, Durham. Statistics textbook for health administration students. Stresses methods relevant to administration such as forecasting and project analysis. Assumes knowledge of algebra, statistics, accounting, economics, and health care organizations.

Methods for Meta-Analysis in Medical Research (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section) Best Reviews

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With meta-analysis methods playing a crucial role in health research in recent years, this important and clearly-written book provides a much-needed survey of the field.
Meta-analysis provides a framework for combining the results of several clinical trials and drawing inferences about the effectiveness of medical treatments. The move towards evidence-based health care and practice is underpinned by the use of meta-analysis. This book:
* Provides a thorough criticism and an up-to-date survey of meta-analysis methods
* Emphasises the practical approach, and illustrates the methods by numerous examples
* Describes the use of Bayesian methods in meta-analysis
* Includes discussion of appropriate software for each analysis
* Includes numerous references to more advanced treatment of specialist topics
* Refers to software code used in the examples available on the authors' Web site
Practising statisticians, statistically-minded clinicians and health research professionals will benefit greatly from the clear presentation and numerous examples. Medical researchers will grasp the basic principles of meta-analysis, and learn how to apply the various methods.

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How can one tell if a new programme has been effective or not? Is there any way to predict how a group of individuals would have fared without the new programme or service? Packed with rich and varied examples, Robert F Boruch's book untangles the complexities of randomized field experiments to enable researchers to evaluate better the impact of new programmes. After an exploration of how to judge whether or not a programme worked, the author discusses: the context of experiments; the standards used to judge the ethical propriety of randomized experiments; methods for studying populations; sampling methods; the randomization procedure; baseline measures; missing data registry; and analyses for quality assurance.

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Dealing with dynamics of processes that repeat themselves regularly, this revised and updated edition extends the thread from 1980 to the present day, concentrating on areas of interest where there will be much activity in the future. This involves going through spatial biochemical, electrophysiological, and organismic dynamical systems and patterns that were discovered by pursuing the theme of phase singularities introduced in the original book. In particular the work on excitability in cell membranes will be thoroughly updated as will the references throughout the book.

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Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics) Reviews

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THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION

Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research.

This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data.

Features of the Second Edition include:

• Expanded coverage of interactions and the covariate-adjusted survival functions
• The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques
• New discussion of variable selection with multivariable fractional polynomials
• Further exploration of time-varying covariates, complex with examples
• Additional treatment of the exponential, Weibull, and log-logistic parametric regression models
• Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values
• New examples and exercises at the end of each chapter

Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.

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The most important techniques available for longitudinal data analysis are discussed in this book. The discussion includes simple techniques such as the paired t-test and summary statistics, but also more sophisticated techniques such as generalized estimating equations and random coefficient analysis. A distinction is made between longitudinal analysis with continuous, dichotomous, and categorical outcome variables. This practical guide is especially suitable for non-statisticians and all those undertaking medical research or epidemiological studies.

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The first edition of Design and Analysis of Cross-Over Trials quickly became the standard reference on the subject and has remained so for more than 12 years. In that time, however, the use of cross-over trials has grown rapidly, particularly in the pharmaceutical arena, and researchers have made a number of advances in both the theory and methods applicable to these trials.

Completely revised and updated, the long-awaited second edition of this classic text retains its predecessor's careful balance of theory and practice while incorporating new approaches, more data sets, and a broader scope. Enhancements in the second edition include:

• A new chapter on bioequivalence
• Recently developed methods for analyzing longitudinal continuous and categorical data
• Real-world examples using the SAS system
• A comprehensive catalog of designs, datasets, and SAS programs available on a companion Web site at www.crcpress.com

The authors' exposition gives a clear, unified account of the design and analysis of cross-over trials from a statistical perspective along with their methodological underpinnings. With SAS programs and a thorough treatment of design issues, Design and Analysis of Cross-Over Trials, Second Edition sets a new standard for texts in this area and undoubtedly will be of direct practical value for years to come.

Buy Applied Meta-Analysis for Social Science Research (Methodology in the Social Sciences)

Applied Meta-Analysis for Social Science Research (Methodology in the Social Sciences) by The Guilford Press

Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs.

 

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Praised in the first edition for the clarity of his general framework for conceptualizing meta-analysis, Rosenthal's revised edition covers the latest techniques in the field, such as a new effect size indicator for one size data, a new coefficient of robustness of replication, new procedures for combining and comparing effect sizes for multiple dependent variables, and new data on the magnitude of the problem of incomplete retrieval (the file drawer problem).

Best Practical Sampling (Applied Social Research Methods)

Practical Sampling (Applied Social Research Methods) by SAGE Publications, Inc

Practical Sampling provides guidance for researchers dealing with the everyday problems of sampling. Using the practical design approach Henry integrates sampling into the overall research design and explains the interrelationships between research and sampling choices. The style is concise and narrative; mathematical presentations are limited to necessary formulas; and calculations are kept to the absolute minimum, making it very approachable for any researcher.

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