Book 2

Queues

by D. R. Cox

Published 1 June 1991
This is a classic book on Queues. First published in 1961 it is clearly and concisely introduces the theory of queueing systems and is still just as relevant today. The monograph is aimed at both students and operational research workers concerned with the practical investigations of queueing, although almost every statistician will find its contents of interest.

Book 12

Point Processes

by D. R. Cox and Valerie Isham

Published 17 July 1980

There has been much recent research on the theory of point processes, i.e., on random systems consisting of point events occurring in space or time. Applications range from emissions from a radioactive source, occurrences of accidents or machine breakdowns, or of electrical impluses along nerve fibres, to repetitive point events in an individual's medical or social history. Sometimes the point events occur in space rather than time and the application here raneg from statistical physics to geography. The object of this book is to develop the applied mathemathics of point processes at a level which will make the ideas accessible both to the research worker and the postgraduate student in probability and statistics and also to the mathemathically inclined individual in another field interested in using ideas and results. A thorough knowledge of the key notions of elementary probability theory is required to understand the book, but specialised "pure mathematical" coniderations have been avoided.


Book 21

Analysis of Survival Data

by D. R. Cox

Published 1 June 1984
This monograph contains many ideas on the analysis of survival data to present a comprehensive account of the field. The value of survival analysis is not confined to medical statistics, where the benefit of the analysis of data on such factors as life expectancy and duration of periods of freedom from symptoms of a disease as related to a treatment applied individual histories and so on, is obvious. The techniques also find important applications in industrial life testing and a range of subjects from physics to econometrics. In the eleven chapters of the book the methods and applications of are discussed and illustrated by examples.

Book 31

This book sets out in detail mathematical techniques valuable for giving useful approximate solutions to a wide range of problems in statistical theory and methods as well as in applied probability. The emphasis throughout is on the relatively simple general concepts involved and on their illustration by a wide range of examples, chosen to be of intrinsic interest. The precise mathematical theorems with their associated, rather formidable technical conditions are given as appendices, but the emphasis in the body of the text is on applications. The first four chapters deal with univariate problems, where the key ideas are seen in their simplest, yet widely useful, form. The last three chapters deal with the corresponding multivariate problems. The notation, especially the use of tensor methods, has been chosen to emphasize the parallel with one dimensional results. In addition to the examples, which are an intrinsic part of the text, there are roughly 100 further results and exercises, many of which outline recent research results. The book is aimed at a number of different types of reader, including advanced statistics and probability students and research workers in these and related fields.

Book 32

Analysis of Binary Data

by D. R. Cox and E. J. Snell

Published 26 March 1970

The first edition of this book (1970) set out a systematic basis for the analysis of binary data and in particular for the study of how the probability of 'success' depends on explanatory variables. The first edition has been widely used and the general level and style have been preserved in the second edition, which contains a substantial amount of new material. This amplifies matters dealt with only cryptically in the first edition and includes many more recent developments. In addition the whole material has been reorganized, in particular to put more emphasis on m.aximum likelihood methods.

There are nearly 60 further results and exercises. The main points are illustrated by practical examples, many of them not in the first edition, and some general essential background material is set out in new Appendices.


Book 52

This book provides a systematic account of some developments in asymptotic parametric inference from a likelihood-based perspective. It focuses on first-order asymptotic theory, and discusses the need for higher-order theory.

Book 67

Large observational studies involving research questions that require the measurement of several features on each individual arise in many fields including the social and medical sciences. This book sets out both the general concepts and the more technical statistical issues involved in analysis and interpretation. Numerous illustrative examples ar

Components of Variance

by D. R. Cox and P.J. Solomon

Published 30 July 2002

Identifying the sources and measuring the impact of haphazard variations are important in any number of research applications, from clinical trials and genetics to industrial design and psychometric testing. Only in very simple situations can such variations be represented effectively by independent, identically distributed random variables or by random sampling from a hypothetical infinite population.

Components of Variance illuminates the complexities of the subject, setting forth its principles with focus on both the development of models for detailed analyses and the statistical techniques themselves. The authors first consider balanced and unbalanced situations, then move to the treatment of non-normal data, beginning with the Poisson and binomial models and followed by extensions to survival data and more general situations. In the final chapter, they discuss ways of extending and assessing various models, including the study of exceedances, the use of nonlinear representations, the study of transformations of the response variable, and the detailed examination of the distributional form of the underlying random variables.

Careful signposting and numerous examples from genetic data analysis, clinical trial design, longitudinal data analysis, industrial design, and meta-analysis make this book accessible - and valuable - not only to statisticians but to all applied research scientists who use statistical methods.


Why study the theory of experiment design? Although it can be useful to know about special designs for specific purposes, experience suggests that a particular design can rarely be used directly. It needs adaptation to accommodate the circumstances of the experiment. Successful designs depend upon adapting general theoretical principles to the spec