STATISTICAL METHODS IN HUMAN DEVELOPMENT/CLINICAL STUDIES

工作总结：该项目旨在开发新的统计方法 解决人类发展中的问题的技术和应用现有的 技术以新颖的方式解决这些问题。工作将在四年内继续进行 研究领域：(1)人类出生体重分布的统计建模 人口，(2)发展轨迹的回归模型 青春期儿童生殖激素的变化，(3)退化 大豆饮食对胆固醇和性激素影响的模拟研究 结合球蛋白，(4)开发检测LOG链接或 Logit链接更适合于给定的数据集。 开发一个令人满意的出生体重分布模型将 有助于更好地理解出生体重与 婴儿死亡率。我们正在将我们开发的模型应用于美国。 出生体重和围产儿死亡率记录，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。 在发现某些非线性回归模型可以节俭地 描述青春期期间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 在显示的规律性程度(使用熵测量进行评估)中 在超过8小时的一系列连续49次血清激素测量中。这个 规则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.