Analysis Longitud Data 2e Osss: Ncs P

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis of longitudinal data, it covers both the underlying statistical theory of each method, and its application to a range of examples from the agricultural and
biomedical sciences. The main topics discussed are design issues, exploratory methods of analysis, linear models for continuous data, general linear models for discrete data, and models and methods for handling data and missing values. Under each heading, worked examples are presented in parallel
with the methodological development, and sufficient detail is given to enable the reader to reproduce the author's results using the data-sets as an appendix. This second edition, published for the first time in paperback, provides a thorough and expanded revision of this important text. It includes
two new chapters; the first discusses fully parametric models for discrete repeated measures data, and the second explores statistical models for time-dependent predictors.


Author: Peter Diggle, Patrick Heagerty, Kung-Yee Liang
Publisher: Oxford University Press, USA
Published: 05/08/2013
Pages: 400
Binding Type: Paperback
Weight: 1.27lbs
Size: 9.10h x 6.10w x 0.90d
ISBN: 9780199676750

About the Author

Peter Diggle, Department of Mathematics and Statistics, University of Lancaster

Patrick Heagerty, Biostatistics department University of Washington

Kung-Yee Liang, Biostatistics department, Johns Hopkins University

Scott Zeger, Biostatistics department, Johns Hopkins University