STATISTICAL METHODS FOR REPRODUCTIVE EPIDEMIOLOGY

目前，生殖流行病学研究的目的是确定 对人类生殖的危害，包括职业危害和 环境风险因素和宿主风险因素。 整个 在这样的研究中记录一对夫妇的怀孕史。 但没过 家庭、妊娠结局不是独立事件。 例如有些 研究表明，在一个家庭中， 与随后胎儿丢失的可能性更大有关。 此外，本发明还提供了一种方法， 这种非独立性也适用于早产等结局， 低出生体重的后代。 因此，统计程序假设 独立的观察可能无法正确解释 结果 在同一个家庭中进行的观察的依赖性很长时间 在动物研究数据分析和方法中得到认可， 在这方面提出了处理问题的建议。 但很少 已经提出了用于分析来自人类的数据的方法， 生殖研究。 建议用于分析动物数据的方法， 多个概念同时暴露，可能不适合 对人类生殖数据的分析， 变量可能因怀孕而异。 其中一种方法是 Kissling（1981）提出的，并应用于职业数据， 生殖研究 这项工作将研究四个广泛的类别的模型用于分析 人类生殖的结果。 参数估计方法和 将开发假设检验，可用于观察结果 不像生殖研究那样是独立的。 的性质 这些估计器和测试将通过大量研究进行广泛研究 蒙特卡罗模拟研究。 这些模型将应用于 现有的职业生殖流行病学数据集， 苯乙烯暴露对生殖功能的影响。 的结果 不同模型的分析以及这些数据的分析 使用简单的逻辑模型设置，忽略了独立性问题， 将被相互比较和对比。

Currently reproductive epidemiology studies are performed to identify hazards to human reproduction, both in terms of occupational and environmental risk factors as well as host risk factors. The entire pregnancy history for a couple is taken in such a study. However, within a family, pregnancy outcomes are not independent events. For instance, some studies have suggested that within a family the occurrence of a fetal loss is associated with greater chance of subsequent fetal loss. In addition, this nonindependence is also true for outcomes such as preterm delivery and for low birth weight offspring. Thus, statistical procedures which assume independent observations may not give the correct interpretation to the results. The dependence of observations made in the same family has long been recognized in the analysis of data from animal studies and methods to deal with the problem in this context have been proposed. However, few methods have been proposed for use in the analysis of data from human reproductive studies. Methods proposed for analysis of animal data, where multiple conceptuses are exposed simultaneously, may not be appropriate for the analysis of human reproductive data in which exposure or other variables may vary from pregnancy to pregnancy. One such method has been proposed by Kissling (1981) and was applied to data from an occupational reproductive study. This work will examine four broad classes of models for use in the analysis of human reproductive outcomes. Methods for parameter estimation and hypothesis testing will be developed that can be used when observations are not independent, as is the case in reproductive studies. The properties of these estimators and tests will be extensively studied through a multitude of Monte Carlo simulation studies. These models will be applied to an existing occupational reproductive epidemiology data set examining the effects of styrene exposure on reproductive function. The results of analyses for the different models as well as for the analysis of this data set using the simple logistic model, which ignores the independence issue, will be compared and contrasted to each other.