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