Xiao Luo, Thurston Sally W, Ruppert David, Love Tanzy M T, Davidson Philip W
Johns Hopkins University, Department of Biostatistics, Baltimore, MD 21205, USA.
University of Rochester, Department of Biostatistics and Computational Biology, Rochester, NY 14642, USA.
J Am Stat Assoc. 2014 Jan 1;109(505):1-10. doi: 10.1080/01621459.2013.830070.
The Seychelles Child Development Study (SCDS) examines the effects of prenatal exposure to methylmercury on the functioning of the central nervous system. The SCDS data include 20 outcomes measured on 9-year old children that can be classified broadly in four outcome classes or "domains": cognition, memory, motor, and social behavior. Previous analyses and scientific theory suggest that these outcomes may belong to more than one of these domains, rather than only a single domain as is frequently assumed for modeling. We present a framework for examining the effects of exposure and other covariates when the outcomes may each belong to more than one domain and where we also want to learn about the assignment of outcomes to domains. Each domain is defined by a sentinel outcome which is preassigned to that domain only. All other outcomes can belong to multiple domains and are not preassigned. Our model allows exposure and covariate effects to differ across domains and across outcomes within domains, and includes random subject-specific effects which model correlations between outcomes within and across domains. We take a Bayesian MCMC approach. Results from the Seychelles study and from extensive simulations show that our model can effectively determine sparse domain assignment, and at the same time give increased power to detect overall, domain-specific and outcome-specific exposure and covariate effects relative to separate models for each endpoint. When fit to the Seychelles data, several outcomes were classified as partly belonging to domains other than their originally assigned domains. In retrospect, the new partial domain assignments are reasonable and, as we discuss, suggest important scientific insights about the nature of the outcomes. Checks of model misspecification were improved relative to a model that assumes each outcome is in a single domain.
塞舌尔儿童发展研究（SCDS）考察了产前接触甲基汞对中枢神经系统功能的影响。SCDS数据包括对9岁儿童测量的20项结果，这些结果大致可分为四个结果类别或“领域”：认知、记忆、运动和社会行为。先前的分析和科学理论表明，这些结果可能属于多个这些领域，而不是像建模时经常假设的那样仅属于单个领域。我们提出了一个框架，用于考察暴露和其他协变量的影响，此时结果可能各自属于多个领域，并且我们还想了解结果在各领域的分配情况。每个领域由一个仅预先指定给该领域的哨兵结果定义。所有其他结果可以属于多个领域，且未预先指定。我们的模型允许暴露和协变量效应在不同领域以及同一领域内的不同结果之间有所不同，并包括随机的个体特异性效应，该效应模拟了领域内和领域间结果之间的相关性。我们采用贝叶斯MCMC方法。塞舌尔研究的结果以及广泛的模拟表明，我们的模型能够有效地确定稀疏的领域分配，同时相对于针对每个终点的单独模型，在检测总体、领域特异性和结果特异性的暴露和协变量效应方面具有更强的能力。当应用于塞舌尔数据时，一些结果被归类为部分属于其最初指定领域之外的其他领域。事后看来，新的部分领域分配是合理的，并且如我们所讨论的，这对结果的性质提出了重要的科学见解。相对于假设每个结果都在单个领域的模型，模型误设的检验得到了改进。
