DEVELOPMENT OF STATISTICAL METHODS FOR PERINATAL DISEASE

围产期疾病统计方法的发展

• 批准号: 2673722
• 负责人: HEPING ZHANG
• 金额: $ 12.5万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-05-01 至 2000-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2673722
• 关键词: computer program /software; congenital disorders; disease /disorder proneness /risk; human data; human morbidity; human mortality; mathematical model; method development; model design /development; perinatal; statistics /biometry

Built upon two advanced nonparametric statistical techniques, Multivariate Adaptive Regression Splines and Classification and Regression Trees, tree-based methods will be developed and applied to explore the data from the Yale Pregnancy Outcome Study (YPOS), which was designed to examine the relationship between pregnancy outcome and a variety of risk factors, including prescription drug and alcohol use, tobacco smoke, caffeine consumption, and contraceptive practice. Data from about 7,000 subjects will be available from two related YPOS's. Analyses will also be extended to several other important databases including the 1988 National Health Interview Survey on Child Health. In contrast to traditional statistical methods and software, the mechanisms that we will employ and investigate have several advantages: (i) automatically finding the important variables and significant interactions among a large number of variables, making it more likely that new risk factors for pregnancy outcome study (other studies as well) will be discovered; (ii) identifying high risk individuals; (iii) efficiently using data by dealing with missing data and predictors of mixed (ordinal, nominal, and nested) types appropriately. We will study pregnancy outcomes associated with perinatal death such as intrauterine growth retardation, small for gestational age, and preterm delivery, and determine the relationship between these outcomes and putative risk factors. Although the YPOS data base has been extensively analyzed using more traditional methods, the tree-based methods will provide a deeper understanding of risk factors, and will therefore impact on the development of plans for public health programs to prevent birth defects. The emphasis of this project will be on interactive effects among risk factors in connection to the outcome of interest (e.g., miscarriage or birthweight). The methods and software developed by this study will offer researchers the opportunity to perform more flexible, realistic, and efficient analyses in epidemiologic studies.

基于两种先进的非参数统计技术，

项目成果

A frailty model of segregation analysis: understanding the familial transmission of alcoholism.

隔离分析的脆弱模型：了解酗酒的家族传播。

• DOI: 10.1111/j.0006-341x.2000.00815.x
• 发表时间: 2000
• 期刊: Biometrics.
• 作者: Zhang,H;Merikangas,K
• 通讯作者: Merikangas,K

Tree-based, two-stage risk factor analysis for spontaneous abortion.

基于树的自然流产两阶段危险因素分析。

• DOI: 10.1093/oxfordjournals.aje.a008869
• 发表时间: 1996
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: Zhang,H;Bracken,MB
• 通讯作者: Bracken,MB

Model for the analysis of binary time series of respiratory symptoms.

用于分析呼吸道症状二元时间序列的模型。

• DOI: 10.1093/oxfordjournals.aje.a010171
• 发表时间: 2000
• 期刊: American journal of epidemiology
• 影响因子: 5
• 作者: Zhang,H;Triche,E;Leaderer,B
• 通讯作者: Leaderer,B

Mapping quantitative trait loci with extreme discordant sib pairs: sampling considerations.

用极端不一致的同胞对绘制数量性状基因座：抽样考虑。

• 发表时间: 1996
• 期刊: American journal of human genetics
• 影响因子: 9.8
• 作者: Risch,NJ;Zhang,H
• 通讯作者: Zhang,H

Mapping quantitative-trait loci in humans by use of extreme concordant sib pairs: selected sampling by parental phenotypes.

通过使用极端一致的同胞对来绘制人类的数量性状基因座：根据亲本表型进行选择抽样。

• 发表时间: 1996
• 期刊: American journal of human genetics
• 影响因子: 9.8
• 作者: Zhang,H;Risch,N
• 通讯作者: Risch,N