Unified Methods for Censored Longitudinal Data and Causality (Springer Series in Statistics)

Laan, Mark J. Van Der J.; Robins, James M

ISBN 10: 1441930558 / ISBN 13: 9781441930552

Published by Springer, 2011

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Bibliographic Details

• Title: Unified Methods for Censored Longitudinal Data and Causality (Springer Series in Statistics)
• Publisher: Springer
• Publication Date: 2011
• Language: English
• ISBN 10: 1441930558
• ISBN 13: 9781441930552
• Binding: Soft cover
• Condition: New

About this title

Synopsis

During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. This book provides a fundamental statistical framework for the analysis of this type of data.

Review

From the reviews:

"This book provides a rigourous statistical framework for the analysis of complex large longitudinal data. It provides a comprehensive description of optimal estimation techniques based on time-dependent data structures ... . This is an excellent book for Ph.D. level students in Biostatistics and Statistics who have a strong background in mathematics. It is also suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data." (Subhash C. Kochar, Sankhya: The Indian Journal of Statistics, Vol. 66 (1), 2004)

"This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures ... . The book can be used to teach masters-level and Ph.D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data." (P. Rochus, Mathematical Reviews, 2003m)

"This book by two major research workers in the field addresses in generality important problems involving multivariate longitudinal data ... . it is an important book dealing with important problems. Therefore, experts in modern semi-parametric theory should certainly read the book. Those with an interest focussed more on applications and able to draw together a reading group with appropriate expertise are very likely to profit greatly from a sustained study of the book." (D.R. Cox, Short Book Reviews, Vol. 23 (2), 2003)