Analysis of ordered categorical data: two score-independent approaches.
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.
Zheng
Gang
G
Office of Biostatistics Research, National Heart, Lung and Blood Institute, Bethesda, Maryland 20892-7913, USA. zhengg@nhlbi.nih.gov
D000015:Abnormalities, Multiple / Q000139:chemically induced; D000428:Alcohol Drinking / Q000009:adverse effects; D001699:Biometry / Q000379:methods*; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008431:Maternal-Fetal Exchange; D009035:Mothers; D011247:Pregnancy; D013223:Statistics as Topic