Regression Methods In Biostatistics

Author: Eric Vittinghoff
Publisher: Springer Science & Business Media
ISBN: 1461413532
Size: 27.38 MB
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This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.

The Evaluation Of Surrogate Endpoints

Author: Geert Molenberghs
Publisher: Springer Science & Business Media
ISBN: 9780387202778
Size: 14.70 MB
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The identification and use of surrogate endpoints, i.e., measures that can replace or supplement other endpoints in evaluations of experimental treatments or other interventions, is a general strategy that has stimulated both enthusiasm and scepticism. This book offers a balanced account on this controversial topic.

Intuitive Biostatistics

Author: Harvey Motulsky
Publisher: Oxford University Press, USA
ISBN: 0199946647
Size: 11.89 MB
Format: PDF, Docs
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Thoroughly revised and updated, the third edition of Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking retains and refines the core perspectives of the previous editions: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. With its engaging and conversational tone, this unique book provides a clear introduction to statistics for undergraduate and graduate students in a wide range of fields and also serves as a statistics refresher for working scientists. It is especially useful for those students in health-science related fields who have no background in biostatistics. NEW TO THIS EDITION * A new chapter on the complexities of probability * A new chapter on meta-analysis * A completely rewritten chapter on statistical traps to avoid * More sections on common mistakes in data analysis * More Q&A sections * New topics and examples * New learning tools (each chapter ends with a summary and a list of statistical terms)

Statistical Modeling For Biomedical Researchers

Author: William D. Dupont
Publisher: Cambridge University Press
ISBN: 1139643819
Size: 80.78 MB
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The second edition of this standard text guides biomedical researchers in the selection and use of advanced statistical methods and the presentation of results to clinical colleagues. It assumes no knowledge of mathematics beyond high school level and is accessible to anyone with an introductory background in statistics. The Stata statistical software package is again used to perform the analyses, this time employing the much improved version 10 with its intuitive point and click as well as character-based commands. Topics covered include linear, logistic and Poisson regression, survival analysis, fixed-effects analysis of variance, and repeated-measure analysis of variance. Restricted cubic splines are used to model non-linear relationships. Each method is introduced in its simplest form and then extended to cover more complex situations. An appendix will help the reader select the most appropriate statistical methods for their data. The text makes extensive use of real data sets available at http://biostat.mc.vanderbilt.edu/dupontwd/wddtext/.

Textbook Of Cancer Epidemiology

Author: Hans-Olov Adami
Publisher: Oxford University Press
ISBN: 0190676841
Size: 64.85 MB
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"Comprehensive and comprehensible, but also encouraging -- informed by the hope and belief that informed its creation." -Cancer Amid sweeping advances in the science and treatment of cancer, the TEXTBOOK OF CANCER EPIDEMIOLOGY offers students and professionals a definitive, systematic resource for understanding the factors affecting all types of human cancer. This fully updated new edition offers an overview of epidemiology's key concepts and methods as they relate to cancer (including the emerging potential of biomarkers) as well as site-specific chapters on individual cancers' natural history, pathology, descriptive epidemiology, and etiology. Taken together, these chapters forge connections between established science and the ongoing evolution of this dynamic field. Crisply and concisely written by an assembly of internationally recognized researchers, the TEXTBOOK OF CANCER EPIDEMIOLOGY offers a superlative introduction to the subject's consensuses and controversies for those embarking on their careers and a ready reference for seasoned professionals.

Primer Of Applied Regression Analysis Of Variance Third Edition

Author: Stanton A. Glantz
Publisher: McGraw Hill Professional
ISBN: 0071822445
Size: 74.19 MB
Format: PDF
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A textbook on the use of advanced statistical methods in healthcare sciences Primer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods. The book has been acclaimed for its user-friendly style that makes complicated material understandable to readers who do not have an extensive math background. The text is packed with learning aids that include chapter-ending summaries and end-of-chapter problems that quickly assess mastery of the material. Examples from biological and health sciences are included to clarify and illustrate key points. The techniques discussed apply to a wide range of disciplines, including social and behavioral science as well as health and life sciences. Typical courses that would use this text include those that cover multiple linear regression and ANOVA. Four completely new chapters Completely updated software information and examples

Dynamical Biostatistical Models

Author: Daniel Commenges
Publisher: CRC Press
ISBN: 1498729681
Size: 46.81 MB
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Dynamical Biostatistical Models presents statistical models and methods for the analysis of longitudinal data. The book focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most of the advanced methods, such as multistate and joint models, can be applied using SAS or R software. The book describes advanced regression models that include the time dimension, such as mixed-effect models, survival models, multistate models, and joint models for repeated measures and time-to-event data. It also explores the possibility of unifying these models through a stochastic process point of view and introduces the dynamic approach to causal inference. Drawing on much of their own extensive research, the authors use three main examples throughout the text to illustrate epidemiological questions and methodological issues. Readers will see how each method is applied to real data and how to interpret the results.

Analysis Of Observational Health Care Data Using Sas

Author: Douglas E. Faries
Publisher: SAS Institute
ISBN: 9781607644248
Size: 24.93 MB
Format: PDF
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This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.

Fundamentals Of Biostatistics

Author: Bernard Rosner
Publisher: Cengage Learning
ISBN: 1133008178
Size: 52.88 MB
Format: PDF, Mobi
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Bernard Rosner's FUNDAMENTALS OF BIOSTATISTICS is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.