Latent variable modeling of longitudinal and multilevel alcohol use data
Latent variable modeling of longitudinal and multilevel alcohol use data
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DOI：
10.15288/jsa.1998.59.399
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发表时间：
1998-07-01
期刊：
影响因子：
--
通讯作者：
Hops, H
中科院分区：
文献类型：
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作者：
Duncan, TE;Duncan, SC;Hops, H
目的：本文演示了隐变量模型在包含嵌套结构的纵向数据中的应用。利用多水平潜伏生长模型(LGM)，对家庭中个体(青少年和父母)4年来的酒精使用水平和酒精使用的发展进行了调查。方法：对435个家庭(435个目标青少年、203个兄弟姐妹和566个父母[168个父亲和398个母亲])的酒精使用情况进行了LGM模型检验。青少年(目标和兄弟姐妹)包括312名男孩和326名女孩，平均(+/-SD)年龄1(T1)为13.69+/-1.95岁。假设家庭成员之间的酒精使用水平和发展是同质的，而家庭之间的酒精使用和发展是不同的。研究还考察了家庭状况(单亲、双亲完整和继父母家庭)和社会经济状况对家庭饮酒水平的影响。结果：继父母家庭、文化程度较低、经济条件较差的家庭饮酒水平较高，且发展较快。结论：研究结果表明，同一家庭中的个人的饮酒情况比不同家庭的个人更相似，家庭饮酒可能会受到家庭层面变量的影响，如家庭状况或SES。这些方法结合了家庭一级的分类，可能会提供关于酒精使用的病因和家庭内和家庭之间酒精使用的风险因素的额外信息。
Objective: This article demonstrates use of a latent variable model for longitudinal data which encompasses nested structures. Using Multilevel Latent Growth Modeling (LGM), levels of alcohol use and development of alcohol use over 4 years were examined among individuals (adolescents and parents) nested within families. Method: An LGM model was tested for alcohol use with a sample of 435 families (435 target adolescents, 203 sibling and 566 parents [168 fathers and 398 mothers]). Adolescents (targets and siblings) comprised 312 boys and 326 girls, with a mean (+/-SD) age at Time 1 (T1) of 13.69 +/- 1.95 years. It was hypothesized that there would be homogeneity in level and development of alcohol use among family members and heterogeneity in alcohol use and development across families. The effects of family status (single-parent, two-parent intact and stepparent families) and socioeconomic status (SES) on family levels of alcohol use were also examined. Results: Results suggested that stepparent families, and less educated and more economically disadvantaged families, had higher family levels of alcohol use and developed in their use of alcohol at a faster rate. Conclusions: Findings suggest that the alcohol use of individuals in the same family is more alike than that of individuals from different families and that family alcohol use may be influenced by family-level variables such as family status or SES. Methods such as those presented, which incorporate family-level clustering, are likely to provide additional information regarding the etiology of alcohol use and risk factors for alcohol use within and across families.