Original articleEvaluation of diagnostic tests with multiple diagnostic categories
References (6)
- et al.
Clinical Epidemiology-The Essentials
(1982) Generalized measures of sensitivity, specificity and predictive value in epidemiologic studies
Am J Epidemiol
(1977)- et al.
The predictive power of diagnostic tests and the effect of prevalence of illness
Arch Gen Psychiat
(1983)
Cited by (15)
Real world-like simulations show efficient predictive power of in vitro skin corrosion tests used as stand-alone and in combination and how can toxicologists take advantage of them
2021, Toxicology in VitroCitation Excerpt :For the SCTs of this paper and before that the test T is performed, the odds of finding an actual positive in the whole population of chemicals is the probability of being of an actual positive which is the Prevalence Pe divided by the probability of not being an actual positive (1-Pe) i.e., Prevalence ÷ (1-Prevalence) = Pe/(1-Pe). This odds is called Pre-Test Odds (i.e. Pre-Test Odds = Pe/(1-Pe)) (Birkett, 1988; Altman and Bland, 1994; Deeks and Altman, 2004). For data under consideration in this paper:
The indication area of a diagnostic test. Part i - Discounting gain and loss in diagnostic certainty
2015, Journal of Clinical EpidemiologyCitation Excerpt :In part II of this study, we demonstrate the consequences of attaching different utilities to the test results for the indication area and diagnostic max [33]. We developed this approach in its most simple form for a binary diagnostic test result (positive or negative) and for a binary disease outcome (diseased or healthy) [41]. The model can be expanded to more complex testing situations, for example, if one has to choose between several tests simultaneously or tests in sequential order.
The meaning of diagnostic test results: A spreadsheet for swift data analysis
2000, Clinical RadiologyIncorporating severity of illness into estimates of likelihood ratios
1990, American Journal of the Medical SciencesGeneralization of the likelihood ratio concept for diagnostic tests with multiple diagnostic categories
1989, Journal of Clinical EpidemiologyOptimum binary cut-off threshold of a diagnostic test: Comparison of different methods using Monte Carlo technique
2014, BMC Medical Informatics and Decision Making