Innovative Spatial Survival Models with Geographically Varying Coefficients

具有地理差异系数的创新空间生存模型

• 批准号: 8431341
• 负责人: Jiajia Zhang
• 金额: $ 6.82万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-17 至 2015-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8431341
• 关键词: Code; Computer software; Data; Data Analyses; Data Set; Environment; Epidemiology; Equilibrium; Failure; Geographic Locations; Individual; Judgment; Louisiana; Malignant Neoplasms; Malignant neoplasm of prostate; Methods; Modeling; National Cancer Institute; Pattern; Performance; Play; Public Health; Research; Research Personnel; Role; SEER Program; South Carolina; Testing; Time; Work; base; flexibility; hazard; innovation; neoplasm registry; population based; public health relevance; residence; simulation; software development; user friendly software

DESCRIPTION (provided by applicant): We will develop a general "extended hazard" spatial survival model to predict geographical effects and geo- graphically varying effects in cancer survival. The proposed model can include the proportional hazards spatial survival model and the accelerated failure time spatial survival model as its special cases. Furthermore, the new model can correctly identify the geographical effects and geographically varying effects in cancer survival. The performance of the proposed model will be evaluated by a comprehensive simulation study. To demonstrate the usage of the proposed model, we will apply the proposed method to analyze prostate cancer within Louisiana from the Surveillance, Epidemiology, and End Results program, and prostate cancer data set from South Carolina Central Cancer Registry (SCCCR). The software development will solve the computational issue in practice and will enable the practitioners and researchers apply the proposed method easily.

描述(申请人提供)：我们将开发一个通用的“扩展危险”空间生存模型来预测癌症生存中的地理效应和地理变化效应。该模型可将比例风险空间生存模型和加速失效时间空间生存模型作为其特例。此外，新的模型可以正确识别地理效应和地理变化对癌症生存率的影响。提出的模型的性能将通过全面的仿真研究进行评估。为了演示建议的模型的使用，我们将应用建议的方法来分析路易斯安那州的前列腺癌，这些前列腺癌来自监测、流行病学和最终结果计划，以及南卡罗来纳州中央癌症登记中心(SCCCR)的前列腺癌数据集。软件开发将解决实际中的计算问题，使实践者和研究人员能够方便地应用所提出的方法。

项目成果

Accelerated hazards model based on parametric families generalized with Bernstein polynomials.

• DOI: 10.1111/biom.12104
• 发表时间: 2014-03
• 期刊: Biometrics
• 影响因子: 1.9
• 作者: Chen Y;Hanson T;Zhang J
• 通讯作者: Zhang J