Jie Chen, Joseph Heyse, Tze Leung Lai

Medical Product Safety Evaluation (eBook, PDF)

Biological Models and Statistical Methods

• Format: PDF

Produktbeschreibung

Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Issues and challenges in the design and analysis of safety studies are covered.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 372
• Erscheinungstermin: 3. September 2018
• Englisch
• ISBN-13: 9781351021975
• Artikelnr.: 54118325

Autorenporträt

Jie Chen is a distinguished scientist at Merck Research Laboratories. He has more than 20 years of experience in biopharmaceutical R&D with research interest in the areas of innovative trial design, data analysis, Bayesian methods, multiregional clinical trials, data mining and machining learning methods, and medical product safety evaluation.

Joseph F. Heyse is a Scientific Assistant Vice President at Merck Research Laboratories, Fellow of the ASA and AAAS, and founding editor of Statistics in Biopharmaceutical Research. He has more than 40 years of experience in pharmaceutical R&D with research interest in safety evaluation and health economics and has more than 70 publications in peer reviewed journals. He is an editor of Statistical Methods in Medical Research.

Tze Leung Lai is the Ray Lyman Wilbur Professor of Statistics, and by courtesy, of Biomedical Data Science and Computational & Mathematical Engineering, and Co-director of the Center for Innovative Study Design at Stanford University. He is a Fellow of the IMS and ASA. His research interest includes sequential experimentation, adaptive design and control, change-point detection, survival analysis, time series and forecasting, multivariate analysis and machine learning, safety evaluation and monitoring. He has published 12 books and 300 articles in peer reviewed journals, and has supervised over 70 PhD theses at Columbia and Stanford Universities.