A critical review of research and reflection in the area of death, with special emphasis on death education. Thought-provoking, often controversial reviews of and reactions to the current general domain of death phenomena--specifically death education--are addressed in this book. The author, skeptical that we can do very much with the phenomenon of death and dying, especially in relation to our efforts at addressing it educationally, explores the philosophical, psychological, socio-cultural, and theoretical aspects and raises critical questions that will challenge proponents of death education. Both advocates and critics of death education in particular, and death research in general, will benefit from this intellectually stimulating volume that sounds a cautionary note, yet offers some positive suggestions for the future of death education. Professionals interested in any aspect of death education will be intrigued by this thorough examination of death education from several perspectives.

Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation of some of the important invited and volunteered presentations made during that conference. The three days and evenings of oral and displayed presentations were arranged into six broad thematic areas. The session themes, the invited speakers and the topics they addressed were as follows: * Generalized Linear Models: Peter McCullagh-"Residual Likelihood in Linear and Generalized Linear Models" * Longitudinal Data Analysis: Nan Laird-"Using the General Linear Mixed Model to Analyze Unbalanced Repeated Measures and Longi tudinal Data" * Spatio---Temporal Processes: David R. Brillinger-"Statistical Analy sis of the Tracks of Moving Particles" * Spatial Data Analysis: Noel A. Cressie-"Statistical Models for Lat tice Data" * Modelling Messy Data: Raymond J. Carroll-"Some Results on Gen eralized Linear Mixed Models with Measurement Error in Covariates" * Future Directions: Peter J.