Bücher der Reihe Oxford Statistical Science Series

Multivariate analysis is necessary whenever more than one characteristic is observed on each individual under study. Applications arise in very many areas of study. This book provides a comprehensive introduction to available techniques for analysing date of this form. This edition includes a survey of developments in the subject.

A reference text in the area of biostatistics (medical statistics). It discusses fully parametric models for discrete repeated measures data. It explores statistical models for time-dependent predictors where there may be feedback between the predictor and response variables.

The analysis of time series data has for many years been a central component of statistical research and practice. Although the theory of linear time series is now well established, that of non-linear time series is still a rapidly developing subject. This book, now available in paperback, is an introduction to some of these developments and the present state of research.

This book is an introductory account of time-series analysis, written from the perspective of an applied statistician with a particular interest in biological applications. Separate chapters cover exploratory methods, the theory of stationary random processes, spectral analysis, repeated measurements, ARIMA modelling, forecasting, and bivariate time-series analysis.

This book describes statistical techniques for the design and evaluation of research studies on medical diagnostic tests, screening tests, biomarkers and new technologies for classification and prediction in medicine.

This text focuses on optimum experimental design using SAS, a powerful software package that provides a complete set of statistical tools including analysis of variance, regression, categorical data analysis, and multivariate analysis. SAS codes, results, plots, numerous figures and tables are provided, along with a fully supported website.