Longitudinal data analysis: a handbook of modern statistical methods

Over the past two decades, there have been many research advances in longitudinal data analysis, which plays a prominent role in the health, social, and behavioral sciences. With contributions from some of the most prominent researchers in this area, 'Longitudinal Data Analysis' addresses the various challenges that arise in analyzing longitudinal data, such as complex random error structures, stochastic time-vary covariates, and missing data. The book covers such topics as parametric modeling, non- and semi-parametric methods, joint modeling, and incomplete data. With datasets and other additional material on a supplemental website, it focuses on how to apply these methods through detailed case studies. Set to become a landmark publication in the field, this comprehensive and thoroughly edited volume is accessible to graduate students, methodologists, and practitioners alike. INDICE: Introduction and Historical Overview. Parametric Modeling of Longitudinal Data. Nonparametric and Semiparametric Methods for Longitudinal Data. Joint Models for Longitudinal Data. Incomplete Data. Index.

• ISBN: 978-1-58488-658-7
• Editorial: Chapman & Hall/CRC Statistics and Mathematics
• Encuadernacion: Cartoné
• Páginas: 618
• Fecha Publicación: 03/09/2008
• Nº Volúmenes: 1
• Idioma: Inglés