Survival Analysis for Epidemiologic and Medical Research

Author: Steve Selvin
Publisher: Cambridge University Press
ISBN: 1139471244
Format: PDF, ePub
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This practical guide to survival data and its analysis for readers with a minimal background in statistics shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts as bias, confounding, independence, and interaction are presented in the context of survival analysis and also are basic components of a broad range of applications. These topics make up essentially a 'second-year', one-semester biostatistics course in survival analysis concepts and techniques for non-statisticians.

Introduction to Epidemiologic Research Methods in Public Health Practice

Author: Susan Bailey
Publisher: Jones & Bartlett Publishers
ISBN: 1449627846
Format: PDF, ePub, Docs
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Tailored for multiple purposes including learning about and being equipped to evaluate research studies, conducting thesis/dissertation/capstone projects, and publishing scientific results, Epidemiologic Research Methods in Public Health Practice covers the full breadth of epidemiologic study designs and topics (case, case-control, and cohort studies).

Genomic Clinical Trials and Predictive Medicine

Author: Richard M. Simon
Publisher: Cambridge University Press
ISBN: 1107008808
Format: PDF, Mobi
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This book focuses on novel approaches that provide a reliable basis for identifying which patients are likely to benefit from each treatment. Aimed at both clinical investigators and statisticians, it covers the development and validation of prognostic and predictive biomarkers and their integration into clinical trials.

Applied Survival Analysis

Author: David W. Hosmer, Jr.
Publisher: John Wiley & Sons
ISBN: 1118211588
Format: PDF
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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.

Applied Survival Analysis

Author: David W. Hosmer, Jr.
Publisher: Wiley-Interscience
ISBN:
Format: PDF, ePub, Docs
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A Practical, Up-To-Date Guide To Modern Methods In The Analysis Of Time To Event Data. The rapid proliferation of powerful and affordable statistical software packages over the past decade has inspired the development of an array of valuable new methods for analyzing survival time data. Yet there continues to be a paucity of statistical modeling guides geared to the concerns of health-related researchers who study time to event data. This book helps bridge this important gap in the literature. Applied Survival Analysis is a comprehensive introduction to regression modeling for time to event data used in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies. While the authors emphasize the proportional hazards model, descriptive methods and parametric models are also considered in some detail. Key topics covered in depth include: * Variable selection. * Identification of the scale of continuous covariates. * The role of interactions in the model. * Interpretation of a fitted model. * Assessment of fit and model assumptions. * Regression diagnostics. * Recurrent event models, frailty models, and additive models. * Commercially available statistical software and getting the most out of it. Applied Survival Analysis is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health-related fields.

Epidemiology Kept Simple

Author: B. Burt Gerstman
Publisher: John Wiley & Sons
ISBN: 111852540X
Format: PDF, Kindle
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Epidemiology Kept Simple introduces the epidemiological principles and methods that are increasingly important in the practice of medicine and public health. With minimum use of technical language it fully explains terminology, concepts, and techniques associated with traditional and modern epidemiology. Topics include disease causality, epidemiologic measures, descriptive epidemiology, study design, clinical and primary prevention trials, observational cohort studies, case-control studies, and the consideration of random and systematic error in studies of causal factors. Chapters on the infectious disease process, outbreak investigation, and screening for disease are also included. The latter chapters introduce more advanced biostatistical and epidemiologic techniques, such as survival analysis, Mantel-Haenszel techniques, and tests for interaction. This third edition addresses all the requirements of the American Schools of Public Health (ASPH) Epidemiological Competencies, and provides enhanced clarity and readability on this difficult subject. Updated with new practical exercises, case studies and real world examples, this title helps you develop the necessary tools to interpret epidemiological data and prepare for board exams, and now also includes review questions at the end of each chapter. Epidemiology Kept Simple continues to provide an introductory guide to the use of epidemiological methods for graduate and undergraduate students studying public health, health education and nursing, and for all practicing health professionals seeking professional development.

Applied Multilevel Analysis

Author: Jos W. R. Twisk
Publisher: Cambridge University Press
ISBN: 0521849756
Format: PDF
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This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians, and they focus on the mathematical background. These books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the application of multilevel analysis in research. It addresses the practical issues that confront those undertaking research and wanting to find the correct answers to research questions. This book is written for non-mathematical researchers and it explains when and how to use multilevel analysis. 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 reanalyse the data. This approach will help to bridge the conceptual and communication gap that exists between those undertaking research and statisticians.

Quantitative Methods for Health Research

Author: Dr. Nigel Bruce
Publisher: John Wiley & Sons
ISBN: 0470022744
Format: PDF, ePub, Docs
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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.

Practical Handbook of Sample Size Guidelines for Clinical Trials

Author: Jonathan J. Shuster
Publisher: CRC Press
ISBN: 9780849344879
Format: PDF, ePub, Mobi
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Practical Handbook of Sample Size Guidelines for Clinical Trials is a concise guide and powerful software utility program that provides a valuable, non-technical blueprint for the design and analysis of survival clinical trials. This text and software allow clinical researchers to write more effective protocols or research grant proposals in a fraction of the time it would take them otherwise. Clinical researchers also gain insight into how biostatisticians analyze trial data and discover what "p-values" really tell them. If you are a biostatistician or student, this book and software will be an indispensable tool for study design. Furthermore, no other book provides justification for survival analysis results at such an introductory level. The program increases your flexibility because it allows you to browse through various planning parameter configurations by changing one parameter at a time, circumventing the need to re-enter the set of planning parameters. Practical Handbook of Sample Size Guidelines for Clinical Trials is ideal for biostatisticians, clinical oncologists, epidemiologists, public health specialists, hematologists, and other researchers who need a concise, easy-to-use tool for sample size determination.