The advances in science and medicine we are now experiencing are unprec edented and exciting. Life expectancy is prolonged, and quality of life is much improved. We learn of fabulous new discoveries made at the bench or the bedside every week. Many diseases have been totally eliminated, others can be significantly improved by new therapeutic formulations. Much of the success can be attributed to a better understanding of disease processes and the specific targeting of new and more effective medications. As is the case in many areas of successful human endeavour, there can be a downside. In the case of drugs and chemicals it is their adverse effects which are of concern. Of course, every effort is made to devise medications that are safe, and the need to elucidate and understand mechanisms are crucial, yet adverse effects remain a problem. They can be unpredictable and diverse. Drugs have been shown to induce virtually the whole gamut of human liver pathology from acute fulminant hepatitis to chronic active hepatitis to cirrho sis and even malignancy. Hence the possibility of adverse drug effects must be considered in the differential diagnosis of many patients with liver disease. This is well recognized and is very important; indeed, removal of the offending agent can often lead to reversal of the adverse effect. This is an area of hepatology where we can really make a difference."

This practical introduction to the analysis of data collected from reliability studies offers clear, detailed explanations of the best and most up-to-date techniques available. Topics include survival analysis with covariates, the assessment of systems performance, reliability growth models, dependency (which encompasses both engineering and statistical approaches), and practical aspects of analysis. A wealth of interesting case studies appear throughout the text, lending "real-world" examples to the more theoretical discussions. Throughout, the authors stress the need for investigators to understand the background and nature of their data if they are to select the most appropriate analysis method. They also provide in-depth treatments of the mathematical and statistical bases underlying each technique. Accessible and comprehensive, the book will be welcomed by students, professionals, and statisticians who are interested in the practical aspects of reliability data analysis.