Applied Longitudinal Data Analysis for Epidemiology, Jos W. R. Twisk

Новое издание

Автор: Twisk Название: Applied Longitudinal Data Analysis for Epidemiology ISBN: 1107699924 ISBN-13(EAN): 9781107699922 Издательство: Cambridge Academ Цена: 5307 р. Наличие на складе: Есть у поставщикаПоставка под заказ. Описание: This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.

Автор: Twisk Название: Applied Longitudinal Data Analysis for Epidemiology ISBN: 110703003X ISBN-13(EAN): 9781107030039 Издательство: Cambridge Academ Рейтинг: Цена: 10825 р. Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.

Автор: Twisk Название: Applied Longitudinal Data Analysis for Epidemiology ISBN: 1107699924 ISBN-13(EAN): 9781107699922 Издательство: Cambridge Academ Рейтинг: Цена: 5307 р. Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.

Описание: Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

Описание: Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

Автор: Rizopoulos Dimitris Название: Joint Models of Longitudinal and Time-to-Event Data ISBN: 1439872864 ISBN-13(EAN): 9781439872864 Издательство: Taylor&Francis Рейтинг: Цена: 7523 р. Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

In follow-up studies it is often of interest to investigate how a longitudinal outcome that is repeatedly measured in time is associated with a time to an event of interest. Typical examples in this setting come from biomarker research, such as HIV studies where longitudinal CD4 cell counts and viral load are collected in conjunction to the time-to-death, and prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence.

This book is the first providing a full treatment of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory focusing on applications of joint modeling, but sufficient mathematical details are provided to facilitate understanding of the key features of these models. All illustrations put forward can be implemented in the R programming language via the freely available package JM written by the author.

Автор: Weir, B.s. Название: Genetic data analysis ISBN: 0878939024 ISBN-13(EAN): 9780878939022 Издательство: Springer Рейтинг: Цена: 5609 р. Наличие на складе: Нет в наличии.

Описание: This revised and expanded second edition of "Genetic Data Analysis" details the statistical methodology needed to draw inferences from discrete genetic data. It includes an expanded treatment of linkage and a chapter on individual identification.

Автор: Mark Woodward Название: Epidemiology: Study Design And Data Analysis ISBN: 1439839700 ISBN-13(EAN): 9781439839706 Издательство: Taylor&Francis Рейтинг: Цена: 7000 р. Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems.

New to the Third Edition

New chapter on risk scores and clinical decision rules

New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputation

New sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines

Many more exercises and examples using both Stata and SAS

More than 60 new figures

After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding.

Web Resource

A wealth of supporting material can be downloaded from the book's CRC Press web page, including:

Real-life data sets used in the text

SAS and Stata programs used for examples in the text

SAS and Stata programs for special techniques covered

Sample size spreadsheet

Автор: Aickin Название: Causal Analysis in Biomedicine and Epidemiology ISBN: 0824707486 ISBN-13(EAN): 9780824707484 Издательство: Taylor&Francis Рейтинг: Цена: р. Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: "Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms. Introduces a new method of model parametritization. Illustrates structural equations and graphical elements for complex causal systems."

Описание: Discusses the application of statistical techniques to various aspects of modern medical research. This book illustrates how these methods prove to be an indispensable part of proper data collection and analysis. It discusses general concepts and the biomedical problem under focus. It details the associated methods, algorithms, and applications.

Автор: Pfeiffer, Dirk U.; Robinson, Timothy P.; Stevenson Название: Spatial Analysis in Epidemiology ISBN: 0198509898 ISBN-13(EAN): 9780198509899 Издательство: Oxford Academ Рейтинг: Цена: 6349 р. Наличие на складе: Поставка под заказ.

Описание: This book provides a practical, comprehensive and up-to-date overview of the use of spatial statistics in epidemiology - the study of the incidence and distribution of diseases. Spatial analytical methods in conjunction with GIS and remotely sensed data can provide insights into the patterns and processes that underlie disease transmission.

Название: Analysis of longitudinal data ISBN: 0199676755 ISBN-13(EAN): 9780199676750 Издательство: Oxford Academ Рейтинг: Цена: 4006 р. Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.

Автор: Sutradhar Название: Dynamic Mixed Models for Familial Longitudinal Data ISBN: 1441983414 ISBN-13(EAN): 9781441983411 Издательство: Springer Рейтинг: Цена: 11219 р. Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides a theoretical foundation for the analysis of discrete data such as count and binary data in the longitudinal setup. Unlike the existing books, this book uses a class of auto-correlation structures to model the longitudinal correlations for the repeated discrete data that accommodates all possible Gaussian type auto-correlation models as special cases including the equi-correlation models. This new dynamic modelling approach is utilized to develop theoretically sound inference techniques such as the generalized quasi-likelihood (GQL) technique for consistent and efficient estimation of the underlying regression effects involved in the model, whereas the existing ‘working’ correlations based GEE (generalizedestimating equations) approach has serious theoretical limitations both for consistent and efficient estimation, and the existing random effects based correlations approach is not suitable to model the longitudinal correlations. The book has exploited the random effects carefully only to model the correlations of the familial data. Subsequently, this book has modelled the correlations of the longitudinal data collected from the members of a large number of independent families by using the class of auto-correlation structures conditional on the random effects. The book also provides models and inferences for discrete longitudinal data in the adaptive clinical trial set up.The book is mathematically rigorous and provides details for the development of estimation approaches under selected familial and longitudinal models. Further, while the book provides special cares for mathematics behind the correlation models, it also presents theillustrations of the statistical analysis of various real life data. This book will be of interest to the researchers including graduate students in biostatistics and econometrics, among other applied statistics research areas. Brajendra Sutradhar is a University Research Professor at Memorial University in St. John’s, Canada. He is an elected member of the International Statistical Institute and a fellow of the American Statistical Association. He has published about 110 papers in statistics journals in the area of multivariate analysis, time series analysis including forecasting, sampling, survival analysis for correlated failure times, robust inferences in generalized linear mixed models with outliers, and generalized linear longitudinal mixed models with bio-statistical and econometric applications. He has served as an associate editor for six years for Canadian Journal of Statistics and for four years for the Journal of Environmental and Ecological Statistics. He has served for 3 years as a member of the advisory committee on statistical methods in Statistics Canada. Professor Sutradhar was awarded 2007 distinguished service award of Statistics Society of Canada for his many years of services to thesociety including his special services for society’s annual meetings.

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