STATISTICAL METHODS IN HUMAN DEVELOPMENT/CLINICAL STUDIES

工作总结：本项目旨在开发新的统计数据， 人类发展问题的技术，并应用现有的 以新颖的方式解决这些问题。 四分钟后继续工作 研究领域：（1）人类出生体重分布的统计建模 人口，（2）发展轨迹的回归建模， 青春期儿童的生殖激素，（3）退化 大豆饮食对胆固醇和性激素影响的模型 结合球蛋白，（4）开发方法，以测试是否日志链接或 logit链接更适合于给定的数据集。 建立一个令人满意的出生体重分布模型将 有助于更好地了解出生体重与 婴儿死亡率。 我们正在将我们开发的模型应用于美国。 出生体重和围产期死亡率记录，以评估死亡率 通过我们的技术测量的分布特征来预测速率。 已经发现某些非线性回归模型可以很吝啬地 描述青春期平均激素水平的变化，我们现在 研究类似的模型可以告诉我们青春期的变化 在规律性的程度（使用熵测量评估）表现出 在一系列的49个连续的血清激素测量超过8小时。 规律性的程度应该随着孩子的成熟而增加。

Summary of Work: This project seeks to develop new statistical techniques for problems in human development and to apply existing techniques to those problems in novel ways. Work continues in four areas: (1) statistical modeling of the birth weight distribution in human populations, (2) regression modeling of developmental trajectories of reproductive hormones in children through puberty, (3) regression modeling of the effects of soy diet on cholesterol and sex hormone binding globulin, (4) developing methods to test whether log link or the logit link is better suited to a given data set. Development of a satisfactory model for birthweight distributions will facilitate a refined understanding of the relationship of birthweight to infant mortality. We are applying a model that we developed to U.S. birthweight and perinatal mortality records to assess how well mortality rates are predicted by distributional features measured by our technique. Having found that certain nonlinear regression models can parsimoniously describe changes in mean hormone levels through puberty, we are now examining what similar models can tell us about changes through puberty in the degree of regularity (assessed using entropy measures) exhibited in a series of 49 consecutive serum hormone measurements over 8 hr. The degree of regularity should increase as children mature.