biostatistical methods the assessment of relative risks wiley series in probability and statistics

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Biostatistical Methods

Author : John M. Lachin
ISBN : 9780470317891
Genre : Mathematics
File Size : 56. 55 MB
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Comprehensive coverage of classical and modern methods of biostatistics Biostatistical Methods focuses on the assessment of risks and relative risks on the basis of clinical investigations. It develops basic concepts and derives biostatistical methods through both the application of classical mathematical statistical tools and more modern likelihood-based theories. The first half of the book presents methods for the analysis of single and multiple 2x2 tables for cross-sectional, prospective, and retrospective (case-control) sampling, with and without matching using fixed and two-stage random effects models. The text then moves on to present a more modern likelihood- or model-based approach, which includes unconditional and conditional logistic regression; the analysis of count data and the Poisson regression model; and the analysis of event time data, including the proportional hazards and multiplicative intensity models. The book contains a technical appendix that presents the core mathematical statistical theory used for the development of classical and modern statistical methods. Biostatistical Methods: The Assessment of Relative Risks: * Presents modern biostatistical methods that are generalizations of the classical methods discussed * Emphasizes derivations, not just cookbook methods * Provides copious reference citations for further reading * Includes extensive problem sets * Employs case studies to illustrate application of methods * Illustrates all methods using the Statistical Analysis System(r) (SAS) Supplemented with numerous graphs, charts, and tables as well as a Web site for larger data sets and exercises, Biostatistical Methods: The Assessment of Relative Risks is an excellent guide for graduate-level students in biostatistics and an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.

Statistical Methods For Immunogenicity Assessment

Author : Harry Yang
ISBN : 9781498700351
Genre : Mathematics
File Size : 26. 86 MB
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Develop Effective Immunogenicity Risk Mitigation StrategiesImmunogenicity assessment is a prerequisite for the successful development of biopharmaceuticals, including safety and efficacy evaluation. Using advanced statistical methods in the study design and analysis stages is therefore essential to immunogenicity risk assessment and mitigation stra

Statistical Analysis Of Designed Experiments

Author : Ajit C. Tamhane
ISBN : 9781118491430
Genre : Science
File Size : 55. 6 MB
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A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests. Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets. With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

Statistical Methods For Survival Data Analysis

Author : Elisa T. Lee
ISBN : 9781118593059
Genre : Mathematics
File Size : 30. 38 MB
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Praise for the Third Edition “. . . an easy-to read introduction to survival analysiswhich covers the major concepts and techniques of thesubject.” —Statistics in Medical Research Updated and expanded to reflect the latest developments,Statistical Methods for Survival Data Analysis, FourthEdition continues to deliver a comprehensive introduction tothe most commonly-used methods for analyzing survival data.Authored by a uniquely well-qualified author team, the FourthEdition is a critically acclaimed guide to statistical methods withapplications in clinical trials, epidemiology, areas of business,and the social sciences. The book features many real-world examplesto illustrate applications within these various fields, althoughspecial consideration is given to the study of survival data inbiomedical sciences. Emphasizing the latest research and providing the mostup-to-date information regarding software applications in thefield, Statistical Methods for Survival Data Analysis, FourthEdition also includes: Marginal and random effect models for analyzing correlatedcensored or uncensored data Multiple types of two-sample and K-sample comparisonanalysis Updated treatment of parametric methods for regression modelfitting with a new focus on accelerated failure time models Expanded coverage of the Cox proportional hazards model Exercises at the end of each chapter to deepen knowledge of thepresented material Statistical Methods for Survival Data Analysis is anideal text for upper-undergraduate and graduate-level courses onsurvival data analysis. The book is also an excellent resource forbiomedical investigators, statisticians, and epidemiologists, aswell as researchers in every field in which the analysis ofsurvival data plays a role.

Multivariate Statistics

Author : Yasunori Fujikoshi
ISBN : 9780470411698
Genre : Mathematics
File Size : 37. 40 MB
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A comprehensive examination of high-dimensional analysis ofmultivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-SampleApproximations is the first book of its kind to explore howclassical multivariate methods can be revised and used in place ofconventional statistical tools. Written by prominent researchers inthe field, the book focuses on high-dimensional and large-scaleapproximations and details the many basic multivariate methods usedto achieve high levels of accuracy. The authors begin with a fundamental presentation of the basictools and exact distributional results of multivariate statistics,and, in addition, the derivations of most distributional resultsare provided. Statistical methods for high-dimensional data, suchas curve data, spectra, images, and DNA microarrays, are discussed.Bootstrap approximations from a methodological point of view,theoretical accuracies in MANOVA tests, and model selectioncriteria are also presented. Subsequent chapters feature additionaltopical coverage including: High-dimensional approximations of various statistics High-dimensional statistical methods Approximations with computable error bound Selection of variables based on model selection approach Statistics with error bounds and their appearance indiscriminant analysis, growth curve models, generalized linearmodels, profile analysis, and multiple comparison Each chapter provides real-world applications and thoroughanalyses of the real data. In addition, approximation formulasfound throughout the book are a useful tool for both practical andtheoretical statisticians, and basic results on exact distributionsin multivariate analysis are included in a comprehensive, yetaccessible, format. Multivariate Statistics is an excellent book for courseson probability theory in statistics at the graduate level. It isalso an essential reference for both practical and theoreticalstatisticians who are interested in multivariate analysis and whowould benefit from learning the applications of analyticalprobabilistic methods in statistics.

Randomization In Clinical Trials

Author : William F. Rosenberger
ISBN : 9781118742372
Genre : Mathematics
File Size : 66. 24 MB
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Praise for the First Edition “All medical statisticians involved in clinical trials should read this book…” - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, simplify the mathematics, and ease readers’ understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition, also published by Wiley.

Statistical Methods In Spatial Epidemiology

Author : Andrew B. Lawson
ISBN : 9781118723173
Genre : Medical
File Size : 43. 98 MB
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Spatial epidemiology is the description and analysis of the geographical distribution of disease. It is more important now than ever, with modern threats such as bio-terrorism making such analysis even more complex. This second edition of Statistical Methods in Spatial Epidemiology is updated and expanded to offer a complete coverage of the analysis and application of spatial statistical methods. The book is divided into two main sections: Part 1 introduces basic definitions and terminology, along with map construction and some basic models. This is expanded upon in Part II by applying this knowledge to the fundamental problems within spatial epidemiology, such as disease mapping, ecological analysis, disease clustering, bio-terrorism, space-time analysis, surveillance and infectious disease modelling. Provides a comprehensive overview of the main statistical methods used in spatial epidemiology. Updated to include a new emphasis on bio-terrorism and disease surveillance. Emphasizes the importance of space-time modelling and outlines the practical application of the method. Discusses the wide range of software available for analyzing spatial data, including WinBUGS, SaTScan and R, and features an accompanying website hosting related software. Contains numerous data sets, each representing a different approach to the analysis, and provides an insight into various modelling techniques. This text is primarily aimed at medical statisticians, researchers and practitioners from public health and epidemiology. It is also suitable for postgraduate students of statistics and epidemiology, as well professionals working in government agencies.

The Analysis Of Covariance And Alternatives

Author : Bradley Huitema
ISBN : 1118067460
Genre : Mathematics
File Size : 60. 46 MB
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A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.

Applied Categorical Data Analysis And Translational Research

Author : Chap T. Le
ISBN : 9780470371305
Genre : Mathematics
File Size : 36. 92 MB
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An updated treatment of categorical data analysis in the biomedical sciences that now explores applications to translational research Thoroughly updated with the latest advances in the field, Applied Categorical Data Analysis and Translational Research, Second Edition maintains the accessible style of its predecessor while also exploring the importance of translational research as it relates to basic scientific findings within clinical practice. With its easy–to–follow style, updated coverage of major methodologies, and broadened scope of coverage, this new edition provides an accessible guide to statistical methods involving categorical data and the steps to their application in problem solving in the biomedical sciences. Delving even further into the applied direction, this update offers many real–world examples from biomedicine, epidemiology, and public health along with detailed case studies taken straight from modern research in these fields. Additional features of the Second Edition include: A new chapter on the relationship between translational research and categorical data, focusing on design study, bioassay, and Phase I and Phase II clinical trials A new chapter on categorical data and diagnostic medicine, with coverage of the diagnostic process, prevalence surveys, the ROC function and ROC curve, and important statistical considerations A revised chapter on logistic regression models featuring an updated treatment of simple and multiple regression analysis An added section on quantal bioassays Each chapter features updated and new exercise sets along with numerous graphs that demonstrate the highly visual nature of the topic. A related Web site features the book′s examples as well as additional data sets that can be worked with using SAS® software. The only book of its kind to provide balanced coverage of methods for both categorical data and translational research, Applied Categorical Data Analysis and Translational Research, Second Edition is an excellent book for courses on applied statistics and biostatistics at the upper–undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the biomedical and public health fields.

Statistical Methods For Rates And Proportions

Author : Joseph L. Fleiss
ISBN : 9781118625613
Genre : Medical
File Size : 36. 44 MB
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"This book is to be recommended as a standard shelf reference . . . and as a ‘must’ to be read by all who wish to better use and understand data involving dichotomous or dichotomizable measurements." —American Journal of Psychiatry In the two decades since the second edition of Statistical Methods for Rates and Proportions was published, evolving technologies and new methodologies have significantly changed the way today’s statistics are viewed and handled. The explosive development of personal computing and statistical software has facilitated the sophisticated analysis of data, putting capabilities that were once the domain of specialists into the hands of every researcher. The Third Edition of this important text addresses these changes and brings the literature up to date. While the previous edition focused on the use of desktop and handheld calculators, the new edition takes full advantage of modern computing power without losing the elegant simplicity that made the text so popular with students and practitioners alike. In authoritative yet clear terminology, the authors have brought the science of data analysis up to date without compromising its accessibility. Features of the Third Edition include: New material on sample size calculations and issues in clinical trials, and entirely new chapters on single-sample data, logistic regression, Poisson regression, regression models for matched samples, the analysis of correlated binary data, and methods for analyzing fourfold tables with missing data The addition of many new problems, both numerical and theoretical Answer sections for numerical problems and hints for tackling the theoretical ones A frequentist approach enhanced by the inclusion of empirical Bayesian methodology where appropriate Combining the latest research with the original studies that established the previous editions as leaders in the field, Statistical Methods for Rates and Proportions, Third Edition will continue to be an invaluable resource for students, statisticians, biostatisticians, and epidemiologists.

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