Statistical Theory and Methodology with Applications to

统计理论和方法及其应用

• 批准号: 7007551
• 负责人: SHYAMAL PEDDADA
• 金额: --
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7007551
• 关键词: carcinogens; dosage; mathematical model; model design /development; statistics /biometry; toxicology

Often NIEHS scientists are interested in studying the effect of a chemical on a tissue or a cell or a gene expression, etc. Accordingly, they conduct suitable dose-response or time-course experiments. Based on the available scientific knowledge, a researcher may hypothesize certain patterns of mean response with respect to dose and/or time. In some instances a researcher may also be interested in detecting the lowest dose or time point at which a significant effect is seen. Usually, the null hypothesis is a flat response and one can express the alternative hypotheses using mathematical inequalities, known as order restrictions, between the unknown parameters of interest. Order restrictions can often be expressed using a graph where each unknown parameter is denoted by a circle, and the inequality, between two unknown parameters, is denoted by an arrow that points towards the larger parameter. Order-restricted statistical inference refers to statistical procedures that take into consideration the order restrictions on the parameter space. The National Toxicology Program (NTP) routinely conducts dose-response studies to investigate the carcinogenic and toxic effects of various chemicals. Using the responses obtained at each dose, the researchers are interested in determining if tumor incidence increases with dose. As another example, in the 90-day pre-chronic toxicity studies, the NTP collects data on a wide range of variables on each animal. For each, the NTP is interested in detecting whether the dose groups have an increased (or decreased) mean response compared to the control group, but there is no prior expectation about the relationships among the doses. In this research program we are developing statistical procedures that can be useful for analyzing data, routinely generated by the researchers are NIEHS, that have the above feature. The new procedures are generally more sensitive than some of the commonly used statistical procedures. We are applying the new procedures for analyzing some of the data obtained by the researchers at NIEHS.

NIEHS的科学家通常对研究化学物质对组织或细胞或基因表达等的影响感兴趣，因此，他们进行适当的剂量反应或时间过程实验。根据现有的科学知识，研究人员可以假设与剂量和/或时间有关的平均反应的某些模式。在某些情况下，研究人员也可能对检测最低剂量或观察到显著效果的时间点感兴趣。通常，零假设是一个平坦的响应，人们可以使用数学不等式来表达备择假设，这些数学不等式被称为顺序限制，在感兴趣的未知参数之间。序限制通常可以使用图来表示，其中每个未知参数由圆圈表示，并且两个未知参数之间的不等式由指向较大参数的箭头表示。序限制统计推断是指考虑参数空间的序限制的统计过程。 国家毒理学计划（NTP）定期进行剂量反应研究，以调查各种化学品的致癌性和毒性作用。使用在每个剂量下获得的反应，研究人员有兴趣确定肿瘤发病率是否随剂量增加而增加。 另一个例子是，在90天慢性毒性前研究中，NTP收集了每只动物各种变量的数据。对于每种情况，NTP都有兴趣检测剂量组与对照组相比是否具有增加（或降低）的平均反应，但没有关于剂量之间关系的先验预期。 在这项研究计划中，我们正在开发统计程序，可以用于分析数据，通常由研究人员产生的NIEHS，具有上述功能。新的程序一般比一些常用的统计程序更敏感。我们正在应用新的程序来分析NIEHS研究人员获得的一些数据。