Latent variable models for teratogenesis using multiple binary outcomes

• 成果类型: Article
• 署名作者: Legler, JM; Ryan, LM
• 署名单位: Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.2307/2291445
• 发表日期: 1997
• 页码: 13-20
• 关键词: repeated categorical measurements; em algorithm; likelihood; tests

摘要

Multiple outcomes are commonly measured in:the study of birth defects. The reason is that most teratogens do not cause a single, uniquely defined defect, but rather result in a range of effects, including major malformations, minor anomalies, and deficiencies in birth weight, length and head circumference. The spectrum of effects associated with a particular teratogen is sometimes described as a ''syndrome.'' In this article we develop a latent variable model to characterize exposure effects on multiple binary outcomes. Not only does the method allow comparisons of control and exposed infants with respect to multiple outcomes, but it also provides a measure of the ''severity'' of each child's condition. Data from a study of the teratogenic effects of anticonvulsants illustrate our results.