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Type I and type II errors. In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. For example, an innocent person may be convicted. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false.
In medical diagnosis, test sensitivity is the ability of a test to correctly identify those with the disease (true positive rate), whereas test specificity is the ability of the test to correctly identify those without the disease (true negative rate). If 100 patients known to have a disease were tested, and 43 test positive, then the test has ...
The specificity of the test is equal to 1 minus the false positive rate. [7] In statistical hypothesis testing, this fraction is given the Greek letter α, and 1 − α is defined as the specificity of the test. Increasing the specificity of the test lowers the probability of type I errors, but may raise the probability of type II errors (false ...
The procedures of Bonferroni and Holm control the FWER under any dependence structure of the p-values (or equivalently the individual test statistics).Essentially, this is achieved by accommodating a `worst-case' dependence structure (which is close to independence for most practical purposes).
False discovery rate. In statistics, the false discovery rate ( FDR) is a method of conceptualizing the rate of type I errors in null hypothesis testing when conducting multiple comparisons. FDR-controlling procedures are designed to control the FDR, which is the expected proportion of "discoveries" (rejected null hypotheses) that are false ...
Variations in healthcare provider training & experience [46] [53] and failure to acknowledge the prevalence and seriousness of medical errors also increase the risk. [54] [55] The so-called July effect occurs when new residents arrive at teaching hospitals, causing an increase in medication errors according to a study of data from 1979 to 2006.
May 24, 2024 at 4:39 PM. By Sriparna Roy and Mariam Sunny. (Reuters) -Advisers to the U.S. health regulator on Friday voted against the use of Novo Nordisk's weekly insulin in patients with type 1 ...
Dissolution testing. In the pharmaceutical industry, drug dissolution testing is routinely used to provide critical in vitro drug release information for both quality control purposes, i.e., to assess batch-to-batch consistency of solid oral dosage forms such as tablets, and drug development, i.e., to predict in vivo drug release profiles. [1]