STATISTICAL METHODS FOR REPRODUCTIVE EPIDEMIOLOGY

目前，进行生殖流行病学研究是为了确定 对人类生殖的危害，无论是在职业上还是在 既有环境风险因素，也有宿主风险因素。整个 一对夫妇的妊娠史就是在这样的研究中被记录下来的。但是，在一个 家庭、妊娠结局不是独立事件。例如，一些 研究表明，在一个家庭中，胎儿丧失的发生 与随后失去胎儿的可能性更大有关。此外, 这种非独立性对于早产和早产等结局也是如此 适用于低出生体重的后代。因此，假设的统计程序 独立的观察可能不会给出正确的解释 结果。长期以来，在同一个家族中所做的观察是相互依赖的 在动物研究和方法的数据分析中得到了认可 已经提出了在这种情况下处理该问题的建议。然而，几乎没有人 已经提出了用于分析人类数据的方法 生殖研究。建议的动物数据分析方法，其中 多个概念同时暴露，可能不适合 对人类生殖数据的分析，其中暴露或其他 不同孕期的变量可能不同。其中一种方法就是 由Kissling(1981)提出，并应用于职业数据 生殖研究。 这项工作将检查分析中使用的四大类模型 人类的生殖结果。参数估计的方法和方法 将开发假设检验，当观察到 不是独立的，就像生殖研究中的情况一样。的属性 这些估计值和检验将被广泛研究。 蒙特卡洛模拟研究。这些模型将应用于 现有的职业生殖流行病学数据集审查 接触苯系物对生殖功能的影响结果是 对不同模型的分析以及对这些数据的分析 使用忽略独立性问题的简单逻辑模型进行设置， 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.