There are many unsolved problems in the study of cancer screening: how to estimate key parameters involved in screening exams, such as screening sensitivity; how to estimate distribution of lead time; how to evaluate the long-term effects of screening, including probability of over diagnosis, true-early-detection and no-early-detection, etc.
Probability Modeling and Statistical Inference in Cancer Screening
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$252.00
Description
There are many unsolved problems in the study of cancer screening: how to estimate key parameters involved in screening exams, such as screening sensitivity; how to estimate distribution of lead time; how to evaluate the long-term effects of screening, including probability of over diagnosis, true-early-detection and no-early-detection, etc.
This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and...
An experienced author in the field of data analytics and statistics, John Macinnes has produced a straight-forward text that breaks down the complex topic of inferential statistics with accessible...
Now updated in a valuable new edition?this user-friendly book focuses on understanding the "why" of mathematical statistics Probability and Statistical Inference, Second Edition introduces key...
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