STATISTICAL METHODS IN HUMAN DEVELOPMENT/CLINICAL STUDIES

这个项目寻求开发新的统计方法 人类发展中的问题技术及其应用 以新的方式解决这些问题的现有技术。工作 在三个方面继续：(1)了解出生体重 在人群中的分布，(2)开发测试方法 无论是LOG链接还是LOGIT链接更适合于给定的数据集， (3)了解年龄、时期和队列对癌症的影响 发病率。我们最近阐明了一个圆整的过程， 从盎司换算成克，并按重量等级分组 这导致了联合航空中一个人为参差不齐的频率多边形 比较100克垃圾桶中显示的出生体重分布 那些来自原始重量单位为克的国家的人。 我们正在开发一个单参数链接函数族，用于 对二元结果进行建模，使数据分析师能够使用 似然比统计，用于检查日志链接或Logit LINK更适合给定的数据集。年龄-时期-队列模型是 通常用于检查癌症随时间的变化 发病率。我们将应用这些模型来分析最近的更新 并研究如何解释这些分析 关于年龄、时期和年龄的线性趋势之间的混淆 模型公式中固有的队列效应。

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 three areas: (1) understanding the birth weight distribution in human populations, (2) developing methods to test whether log link or the logit link is better suited to a given data set, (3) understanding age, period, and cohort effects on cancer incidence. We have recently elucidated a process of round-off, conversion from ounces to grams, and grouping into weight classes that induces an artifactually jagged frequency polygon in United States birth weight distributions displayed in 100-g bins compared to those from countries where the original weight units are grams. We are developing a one-parameter family of link functions for modeling binary outcomes that allow the data analyst to use likelihood ratio statistics to examine whether a log link or a logit link better suits a given data set. Age-period-cohort models are commonly used to examine changes through time in cancer incidence. We will apply these models to analyze the recent update of the SEER data and examine how to interpret such analyses in light of the confounding among linear trends in age, period, and cohort effects inherent in the model formulation.