Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, U.S.A.
Stat Med. 2014 Feb 10;33(3):361-75. doi: 10.1002/sim.5948. Epub 2013 Sep 6.
Studies examining the relationship between neighborhood social disorder and health often rely on multiple informants. Such studies assume interchangeability of the latent constructs derived from multiple-informant data. Existing methods examining this assumption do not clearly delineate the uncertainty at individual levels from that at neighborhood levels. We propose a multilevel variance component factor model that allows this delineation. Data come from a survey of a representative sample of children born between 1983 and 1985 in the inner city of Detroit and nearby middle-class suburbs. Results indicate that the informant-level models tend to exaggerate the effect of places because of differences between persons. Our evaluations of different methodologies lead to the recommendation of the multilevel variance component factor model whenever multiple-informant reports can be aggregated at a neighborhood level.
研究邻里社会失序与健康之间的关系的学者，往往依赖多位信息提供者。这些研究假设，从多位信息提供者所取得的潜在结构是可互换的。现有的检验此假设的方法，并未清楚地区分个别层级与邻里层级的不确定性。我们提出多层次变异数成分因素模式，以进行这样的区分。资料来自 1983 至 1985 年间在底特律市区与附近中产阶级郊区出生的代表性样本儿童的调查。结果显示，由于人与人之间的差异，信息提供者层级的模式倾向夸大地方的效应。我们对于不同方法学的评估，导致当多位信息提供者的报告可在邻里层级上加以汇总时，推荐使用多层次变异数成分因素模式。
