GOLDmineR: improving models for classifying patients with chest pain
Document Type
Article
Publication Title
The Yale journal of biology and medicine
Abstract
The laboratory is dealing with reporting tests as information needed to make clinical decisions. The traditional statistical quality control measures which assigns reference ranges based on 95 percent confidence intervals is insufficient for diagnostic tests that assign risk. We construct a basis for risk assignment by a method that builds on the 2 x 2 contingency table used to calculate the C2 goodness-of-fit and Bayesian estimates. The widely used logistic regression is a subset of the regression method, as it only considers dichotomous outcome choices. We use examples of multivalued predictor(s) and a multivalued as well as dichotomous outcome. Outcomes analyses are quite easy using the ordinal logit regression model.
First Page
183
Last Page
98
Publication Date
1-1-2002
Recommended Citation
Bernstein, Larry; Bradley, Keith; and Zarich, Stuart, "GOLDmineR: improving models for classifying patients with chest pain" (2002). Randomized Controlled Trial. 44.
https://scholar.bridgeporthospital.org/randomized_trial/44
Identifier
12784968 (pubmed); PMC2588788 (pmc)