Bøger i Chapman & Hall/CRC Handbooks of Modern Statistical Methods serien

Focuses on the assorted challenges that arise in analyzing longitudinal data. This book explores four broad themes: parametric modeling, nonparametric and semi parametric methods, joint models, and incomplete data. It is suitable for those involved in the development of statistical methodology or the analysis of longitudinal data.

Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.

Brings together the major advances that have occurred over the years while incorporating enough introductory material for new users of Markov Chain Monte Carlo. Along with coverage of the theoretical foundations and algorithmic and computational methodology, this handbook also includes case studies that demonstrate the application of MCMC methods.

This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering, and other areas.

This handbook presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. The book examines the advantages and limitations of the various modeling techniques and keeps probabilistic, technical details to a minimum. While the book focuses on time series of counts, some of the methods discussed can be applied to other types of discrete-valued time series, such as binary-valued or categorical time series.

This handbook explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective. Top epidemiologists, geographers, and statisticians share interdisciplinary viewpoints on analyzing spatial data and space¿time variations in disease incidences. The book explores the use of GIS and spatial statistics as tools for the analysis of spatial epidemiological data. It covers methodological advances as well as applications in human and veterinary epidemiology. A supplementary website provides color figures, program code, and datasets.

This handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport (baseball, football, hockey, basketball, and soccer) followed by a section on other sports and general statistical design and analysis issues that are common to all sports. This handbook has the potential to become the standard reference for obtaining the necessary background to conduct serious statistical analyses for sports applications and to appreciate scholarly work in this expanding area.