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Updated: Jan 19, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Analysis of ordered categorical data: two score-independent approaches
1Office of Biostatistics Research, National Heart, Lung and Blood Institute, Bethesda, Maryland 20892-7913, USA. zhengg@nhlbi.nih.gov
Summary:
A trend test is often employed to analyze ordered categorical data, in which a set of increasing scores is assigned a priori. There is a drawback in this approach, because how to choose a set of scores is not clear. There have been debates on which scores should be used (e.g., Graubard and Korn, 1987, Biometrics 43, 471-476; Ivanova and Berger, 2001, Biometrics 57, 567-570; Senn, 2007, Biometrics 63, 296-298). Conflicting conclusions are often obtained with different sets of scores. Two approaches, which have been applied to genetic case-control studies, are appealing for ordered categorical data, because they take into account the natural order in the data, are score independent, and not contingent on asymptotic theory. These two approaches are applied to a prospective study for detecting association between maternal drinking and congenital malformations.
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