Analysis of Longitudinal Data

Analysis of Longitudinal Data

The new edition of this important text has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving and important area of biostatistics. Two new chapters have been added on fully parametric models for discrete repeated measures data and on statistical models for time-dependent predictors where there may be feedback between the predictor and response variables. It also contains the many useful features of the previous edition such as, design issues, exploratory methods of analysis, linear models for continuous data, and models and methods for handling data and missing values. "...it is well written, with wide coverage of biological and medical applications. It should continue to have a prominent place in libraries, and researchers who are interested in longitudinal data analysis will want a personal copy." -- Journal of the American Statistical Association The new edition of this important text has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving and important area of biostatistics. Peter Diggle is in the Department of Mathematics and Statistics, University of Lancaster. Patrick Heagerty is in the Biostatistics Department, University of Washington. Kung-Yee Liang and Scott Zeger are both in the Biostatistics Department, Johns Hopkins University. Orders are despatched from our UK warehouse next working day.