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

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Автор: Jos W. R. Twisk
Название:  Applied Longitudinal Data Analysis for Epidemiology
Перевод названия: Анализ данных в эпидемиологии
ISBN: 9780521525800
Издательство: Cambridge Academ
ISBN-10: 0521525802
Обложка/Формат: Paperback
Страницы: 320
Вес: 0.51 кг.
Дата издания: 27.03.2003
Язык: English
Иллюстрации: 54 b/w illus. 159 tables
Размер: 247 x 174 x 17
Читательская аудитория: Professional & vocational
Подзаголовок: A practical guide
Ссылка на Издательство: Link
Поставляется из: Англии
Описание: In this book the most important techniques available for longitudinal data analysis are discussed. This discussion includes simple techniques such as the paired t-test and summary statistics, but also more sophisticated techniques such as generalised estimating equations and random coefficient analysis. A distinction is made between longitudinal analysis with continuous, dichotomous, and categorical outcome variables. It should be stressed that the emphasis of the discussion lies on the interpretation of the different techniques and on the comparison of the results of different techniques. Furthermore, special chapters will deal with the analysis of two measurements, experimental studies and the problem of missing data in longitudinal studies. Finally, an extensive overview of (and a comparison between) different software packages is provided. It is important to realise that this book is a practical guide and especially suitable for non-statisticians.
Дополнительное описание: Epidemiology, public health and medical statistics

      Новое издание

Joint Models of Longitudinal and Time-to-Event Data

Автор: Rizopoulos Dimitris
Название: Joint Models of Longitudinal and Time-to-Event Data
ISBN: 1439872864 ISBN-13(EAN): 9781439872864
Издательство: Taylor&Francis
Цена: 12631 р.
Наличие на складе: Есть у поставщика Поставка под заказ.


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.

Epidemiology: Study Design And Data Analysis

Автор: Mark Woodward
Название: Epidemiology: Study Design And Data Analysis
ISBN: 1439839700 ISBN-13(EAN): 9781439839706
Издательство: Taylor&Francis
Цена: 12341 р.
Наличие на складе: Есть у поставщика Поставка под заказ.


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
Analysis of longitudinal data

Название: Analysis of longitudinal data
ISBN: 0199676755 ISBN-13(EAN): 9780199676750
Издательство: Oxford Academ
Цена: 8395 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.

Causal Analysis in Biomedicine and Epidemiology

Автор: Aickin
Название: Causal Analysis in Biomedicine and Epidemiology
ISBN: 0824707486 ISBN-13(EAN): 9780824707484
Издательство: Taylor&Francis
Цена: 29040 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."

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