By Ying Lu, Jiqian Fang, Lu Tian, Hua Jin
This booklet provides new and strong complex statistical tools which were utilized in sleek medication, drug improvement, and epidemiology. a few of these tools have been firstly built for tackling clinical difficulties. All 29 chapters are self-contained. every one bankruptcy represents the recent improvement and destiny study themes for a clinical or statistical department. For the good thing about readers with assorted statistical heritage, each one bankruptcy follows an analogous variety: the reason of clinical demanding situations, statistical principles and methods, statistical tools and methods, mathematical feedback and historical past and reference. All chapters are written by means of specialists of the respective issues.
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5 We use angiography as the gold standard for coronary artery disease. Assume the actual sensitivity of the radiographic procedure (which we need to estimate) is 80%. Thus, 20% of all diseased patients will have false-negative test results. Suppose 500 patients with coronary artery disease undergo the stress test; 400 respond positively and 100 respond negatively. Since angiography is a risky and expensive procedure, instead of verifying all tested patients by angiography, only 75% of patients with a positive test undergo angiography, and 10% of patients with a negative test undergo angiography.
While the validity of Zhou’s approach relies on the assumption that the disease verification process depends on only the test results and other observed covariates, but not on the disease status, its validity does not require modeling the diseased verification process. However, his approach assumes that the effects of covariates on disease follow a logistic regression model. Baker implemented his approach by first starting with an EM algorithm and then switching to the Newton–Raphson algorithm after a few iterations,15 and Zhou implemented his method using the Newton–Raphson algorithm.
Mathematics and statistics were used in modeling and analysis of infectious epidemic data. Modern statistical methods were developed to investigate the epidemics of non-infectious diseases in the last half of the 20th century. Epidemiological research has become another field of statistical application. It has merged with statistical survey methods to carry out surveillance and disease monitoring, and it is called population science, in contrast to clinical and laboratory sciences. In every field of medical research, statistical thinking and methods are used to provide insight to the data and to verify the hypotheses.