Applied Longitudinal Analysis PDF

Rating: Author: Garrett M. Fitzmaurice ISBN : Product Detai New from Format: PDF

Direct download links available PRETITLE Applied Longitudinal Analysis POSTTITLE from mediafire, rapishare, and mirror link Praise for the First Edition

". . . [this book] should be on the shelf of everyone interested in . . . longitudinal data analysis."
—Journal of the American Statistical Association

 

Features newly developed topics and applications of the analysis of longitudinal data

Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of longitudinal data that can be applied across various fields of study, from the health and medical sciences to the social and behavioral sciences.

The authors incorporate their extensive academic and research experience along with various updates that have been made in response to reader feedback. The Second Edition features six newly added chapters that explore topics currently evolving in the field, including:

• Fixed effects and mixed effects models

• Marginal models and generalized estimating equations

• Approximate methods for generalized linear mixed effects models

• Multiple imputation and inverse probability weighted methods

• Smoothing methods for longitudinal data

• Sample size and power

Each chapter presents methods in the setting of applications to data sets drawn from the health sciences. New problem sets have been added to many chapters, and a related website features sample programs and computer output using SAS®, Stata®, and R, as well as data sets and supplemental slides to facilitate a complete understanding of the material.

With its strong emphasis on multidisciplinary applications and the interpretation of results, Applied Longitudinal Analysis, Second Edition is an excellent book for courses on statistics in the health and medical sciences at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for researchers and professionals in the medical, public health, and pharmaceutical fields as well as those in social and behavioral sciences who would like to learn more about analyzing longitudinal data.

 

 

 

 

 

 

 

Direct download links available for PRETITLE Applied Longitudinal Analysis POSTTITLE

• Product Details
• Table of Contents
• Reviews

• File Size: 5544 KB
• Print Length: 740 pages
• Publisher: Wiley; 2 edition (October 23, 2012)
• Sold by: Amazon Digital Services, Inc.
• Language: English
• ASIN: B009WU0YYG
• Text-to-Speech: Enabled
• X-Ray:
  Not Enabled
• Lending: Enabled
• Amazon Best Sellers Rank: #634,189 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
  • #86 in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Professional Science > Biological Sciences > Biostatistics
• #86 in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Professional Science > Biological Sciences > Biostatistics

Applied Longitudinal Analysis PDF

While the text by Diggle, Heagerty, Liang and Zeger now in its second edition is the first and in my opinion still the best book to cover the theory and methods of longitudinal data analysis, the subject has such great importance in biostatistics and clinical trial research that a number of excellent competitors have now come. This text is certainly one.

Nan Laird and James Ware are Harvard Professors of Biostatistics with a great deal of experience studying and publishing research on longitudinal data. Along with Fitzmaurice they have put together a book that provides a strong foundation in the methodology and a wealth of applications based on their experience.

By Michael R. Chernick

If you need to do longitudinal analyses, and have a moderate mathermatical background, this is a book you should get, particularly if you use SAS. The authors present a wide variety of models clearly, describe their advantages and disadvantages, and illustrate how to use SAS to fit them. They keep the technical level modest (a little use of matrix algebra, but no calculus; not in theorem-proof style) while not sacrificing needed detail. In addition, they provide, at the end of each chapter, two sets of references: One at a similar level to this book, and one with more advanced material for those who wish (and are able) to explore it.

By Peter Flom