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Absolute Risk
Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients, devising public health strategies, and clinical management. The book provides sufficient technical detail to allow statisticians, epidemiologists, and clinicians to build, test, and apply models of absolute risk. Features: Provides theoretical basis for modeling absolute risk, including competing risks and cause-specific and cumulative incidence regression Discusses various sampling designs for estimating absolute risk and criteria to evaluate models Provides details on statistical inference for the various sampli...
Scientific Directory and Annual Bibliography
Presents the broad outline of NIH organizational structure, theprofessional staff, and their scientific and technical publications covering work done at NIH.
Immunodiagnosis of Cancer
Updated to reflect changes in the field since publication of the first edition in 1979. Provides a detailed review of the methodology available for assessing the diagnosis and prognosis of cancer patients including data on the application of tumor marker assays and other immunodiagnostic procedures
Modern Statistical Methods in Chronic Disease Epidemiology
Proceedings of a conference sponsored by the SIAM Institute for Mathematics and Society, and supported by the Department of Energy. Brings together recent developments in the statistical methodology for chronic disease epidimiology. The contributors are all at the forefront of biostatistics research.
Medical Risk Prediction Models
Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient’s individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest. Features: All you need to know to correctly make an online risk c...
