Cargando…
ROC curve regression analysis: the use of ordinal regression models for diagnostic test assessment.
Diagnostic tests commonly are characterized by their true positive (sensitivity) and true negative (specificity) classification rates, which rely on a single decision threshold to classify a test result as positive. A more complete description of test accuracy is given by the receiver operating char...
Autores principales: | Tosteson, A N, Weinstein, M C, Wittenberg, J, Begg, C B |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
1994
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1566538/ https://www.ncbi.nlm.nih.gov/pubmed/7851336 |
Ejemplares similares
-
Variable Selection in ROC Regression
por: Wang, Binhuan
Publicado: (2013) -
Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis
por: Harrell , Jr , Frank E
Publicado: (2015) -
ROC Solid: Receiver Operator Characteristic (ROC) Curves as a Foundation for Better Diagnostic Tests
por: Junge, Mark R. J., et al.
Publicado: (2018) -
Ordinal Logistic Regression in Medical Research
por: Bender, Ralf, et al.
Publicado: (1997) -
Cumulative ROC curves for discriminating three or more ordinal outcomes with cutpoints on a shared continuous measurement scale
por: deCastro, B. Rey
Publicado: (2019)