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Statistical Methods In Assessing Agreement Models Issues And Tools

Sign up here to access free tools such as favorites and notifications, or to access personal subscriptions This book is aimed at a wide range of statisticians, researchers, practitioners, and students in fields such as biomedical equipment, psychology, medical research, and others that require an evaluation of the agreement. Many illustrative practical examples are presented throughout the book in a variety of situations for continuous and categorical data. Dr. Lawrence I. Lin is a Senior Scientist at Baxter International Inc. in the Department of Biostatistics. He is also an Associate Professor in the Department of Mathematics, Statistics and Computer Science at the University of Illinois at Chicago. More than thirty years of consulting experience in clinical studies, research and development (mainly animal toxicity and physiology studies), test validation and method comparisons, product reliability, laboratory quality control (QC), virus screening and inactivation process, pharmacokinetics, market research, litigation, outcome studies, product stability, trend of rare events (signal detection) and evaluation of agreements. His research priorities include agreement evaluation, surveillance strategies, data transformation, discrimination analysis, clinical trial design, medical and pharmaceutical statistics, linear and non-linear modeling, and robust statistics.

He has published on 30 articles in traditional journals. Dr. Lin is a Fellow of the American Statistical Association and an elected member of the International Statistical Institute. He has been an expert on numerous international journals, including Journal of American Statistical Association, Biometrics, Statistics in Medicines, Communication in Statistics, Journal of Biopharmaceutical Statistics, Journal of Applied Statistics, Journal of Probability, and Statistics, to name a few. A.S. Hedayat is a Distinguished Professor of Statistics and Senior Scholar in the Department of Mathematics, Statistics and Computer Science at the University of Illinois at Chicago. His research priorities and statistical advice include experiment planning, medical and pharmaceutical statistics, environmental statistics, forensic statistics, surveillance strategies, agreement evaluation and sample survey. In addition to the traditional publications of more than 160 articles, he has also co-authored three statistical books. Professor Hedayat is a Fellow of the Institute of Mathematical Statistics, a Fellow of the American Statistical Association, and an elected member of the International Statistical Institute. He has been a member of the editorial boards of numerous international journals, including The Annals of Statistics, American Statistical Association and The American Statisticians and the Bulletin of Iranian Mathematical Society.

Compliance measures are required to assess the acceptance of a new or generic process, methodology and formulation in the areas of laboratory performance, instrument or test validation, method comparisons, statistical process control, t quality and individual bioequivalence. . . .