STATISTICAL METHODS IN HUMAN DEVELOPMENT/CLINICAL STUDIES

该项目旨在为解决问题制定新的统计方法。 并将现有方法应用于这些领域 以新颖的方式解决问题。继续在两个领域开展工作：（1）统计 人口中出生体重分布的建模，以及 (2)生殖激素血清浓度的统计建模 在青春期前后的儿童中，（第二个工作领域将被缩减 因为一位重要的合作者佩内洛普·K博士Manasco，离开NIEHS， 6月底）。 发展一个令人满意的统计模型， 人口的出生体重将有助于更好地理解 出生体重与婴儿死亡率的关系。 我们已经开发 一种模型和用于将该模型拟合到数据的方法， 对出生体重分布的粗略描述， 这应该是有用的调查社会和环境 对出生体重的影响 垂体促性腺激素和性腺激素的血清谱显示 不规则间距的明显峰。 适当的统计 模型，人们可以用很少的参数来描述这些轮廓， 青春期发育正常和异常受试者之间的比较 并提供了对发育障碍机制的深入了解。 我们 正在评估一些成年人或动物的模型， 激素，看看他们是否提供了足够的描述， 青春期前儿童的激素水平，但我们还没有找到一个模型， 在几种激素中表现良好。

This project seeks to develop new statistical methodologies for problems in human development and to apply existing methodologies to those problems in novel ways. Work continues in two areas: (1) statistical modeling of the distribution of birthweights in human populations, and (2) statistical modeling of serum concentrations of reproductive hormones in peripubertal children, (The second area of work will be curtailed since an important collaborator, Dr. Penelope K. Manasco, left NIEHS at the end of June). Development of a satisfactory statistical model for the distribution of birth weights in a population will facilitate a refined understanding of the relationship of birthweight to infant mortality. We have developed both a model and a method for fitting the model to data which permit a parsimonious description of a birthweight distribution, a description which should be useful in investigating social and environmental influences on birthweight. Serum profiles of pituitary gonadotropins and gonadal hormones exhibit distinct peaks with irregular spacings. With an appropriate statistical model, one could describe these profiles with few parameters, allowing comparisons among subjects with normal and abnormal pubertal development and providing insight into mechanisms of dysfunctional development. We are evaluating a few models for adult or animal profiles for particular hormones to see whether they provide adequate descriptions for a variety of hormones in prepubertal children, but we have not yet found a model that performs well across several hormones.