IMPROVING THE RISK ASSESSMENT IN EPIDEMIOLOGY

改进流行病学的风险评估

• 批准号: 2521395
• 负责人: HUSSNI O MOHAMMED
• 金额: $ 4.6万
• 依托单位: CORNELL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-12-04 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/2521395
• 关键词: analytical method; animal data; animal population study; cow; data collection methodology /evaluation; epidemiology; horses; infection; life cycle; longitudinal animal study; statistics /biometry; veterinary medicine

The overall goal of the project is to complement the principal investigator's epidemiologic analytical skills by providing an environment for continued development as a veterinary epidemiologist capable of addressing complex analytical issues competently and confidently. The specific aims are: 1) Broaden my knowledge of analytical epidemiologic techniques, namely, the application of random effect models to observations (including serial observations) with binary outcomes. The principal investigator will travel to Maisons Alfort to interact with a group of scientists who have a vast experience with the application of random effect models to veterinary data analysis. 2) Working with Dr. Sanaa and his colleagues, assess the impact of the presence of intra-group correlation on risk identification among observations collected in distinct veterinary epidemiologic studies involving herds of cattle and horses in stables. All these studies investigate etiologic agents that are known to pose hazards to human health: Cryptospordium, Giardia, and Leptospira. The intra-group correlation (herds of cows, horse in a stable) will be estimated from the binary data random effect models. 3) Evaluate the strengths and the limitations of the three currently developed binary data random effect (BDRE) models in risk analysis. These BDRE are the logistic-binomial, logistic-normal, and the probit normal. The goodness of fit for each type of model when applied to each if these data will be compared. The characteristics of a data set that suggest the usage of one model over another will be identified. This evaluation will be carried out on the data that have already been collected in the US and data available in France. 4) Learn the approaches to the analysis of survival data including the use of fraility models.

该项目的总体目标是补充校长 调查员通过提供一个流行病学分析技能 作为兽医流行病学家的持续发展环境 能够能够有效地解决复杂的分析问题 自信。 具体目的是：1）扩大我对 分析流行病学技术，即随机应用 效应模型与观察（包括串行观察）的效果模型 二进制结果。 首席调查员将前往Maisons 与一群经验丰富的科学家互动的Alfort 随机效应模型在兽医数据中的应用 分析。 2）与Sanaa博士及其同事合作，评估 存在组内相关性对风险识别的影响 在不同的兽医流行病学中收集的观察结果中 涉及马s中的牛和马的研究。 所有这些 研究调查了已知对危害构成危害的病因学剂 人类健康：隐秘，贾第鞭毛虫和钩端螺旋体。组内 相关性（牛群，马stable中的马）将从 二进制数据随机效应模型。 3）评估优势和 这三个当前开发二进制数据随机效应的局限性 （BDRE）风险分析中的模型。 这些bdre是逻辑性的， 逻辑正常和概率正常。 适合每个人的优点 如果要比较这些数据，则将模型的类型应用于每个模型。这 暗示使用一种模型的数据集的特征 将确定另一个。 此评估将在 在美国已经收集的数据以及可用的数据 法国。 4）学习分析生存数据的方法 包括使用脆弱模型。