Amazon cover image
Image from Amazon.com

Missing data in longitudinal studies: strategies for Bayesian modeling and sensitivity analysis

By: Contributor(s): Series: Monographs on statistics and applied probability: 109Publication details: Boca Raton Chapman and Hall/CRC Press 2008 Description: xx, 303 pISBN:
  • 9781584886099
Subject(s): DDC classification:
  • 519.5
Summary: This book focuses on how to handle missing data in longitudinal studies, offering specific coverage of models for longitudinal data, missing data mechanisms, and various approaches to sensitivity analysis. It presents an overview of state-of-the-art methods for dealing with missing data, with particular emphasis on handling dropout and causal inference. Many examples, case studies, and applications from the medical sciences support the discussions. The authors use WinBUGS and R to execute the methods and provide datasets and code for download from the Internet. This book stands apart by virtue of the authors' Bayesian approach to inference along with their emphasis on missing data. Source: http://search.barnesandnoble.com
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Item location Shelving location Call number Status Date due Barcode
Books Vikram Sarabhai Library Rack 28-B / Slot 1410 (0 Floor, East Wing) General Stacks 519.5 D2M4 (Browse shelf(Opens below)) Available 167073

Includes bibliographical references (p. 271-291) and indexes.

This book focuses on how to handle missing data in longitudinal studies, offering specific coverage of models for longitudinal data, missing data mechanisms, and various approaches to sensitivity analysis. It presents an overview of state-of-the-art methods for dealing with missing data, with particular emphasis on handling dropout and causal inference. Many examples, case studies, and applications from the medical sciences support the discussions. The authors use WinBUGS and R to execute the methods and provide datasets and code for download from the Internet. This book stands apart by virtue of the authors' Bayesian approach to inference along with their emphasis on missing data. Source: http://search.barnesandnoble.com

There are no comments on this title.

to post a comment.