...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Statistics in medicine >Analyzing discrete competing risks data with partially overlapping or independent data sources and nonstandard sampling schemes, with application to cancer registries
【24h】

Analyzing discrete competing risks data with partially overlapping or independent data sources and nonstandard sampling schemes, with application to cancer registries

机译：分析分离竞争风险数据，具有部分重叠或独立数据源和非标准采样方案，应用于癌症注册管理机构

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper demonstrates the flexibility of a general approach for the analysis of discrete time competing risks data that can accommodate complex data structures, different time scales for different causes, and nonstandard sampling schemes. The data may involve a single data source where all individuals contribute to analyses of both cause‐specific hazard functions, overlapping datasets where some individuals contribute to the analysis of the cause‐specific hazard function of only one cause while other individuals contribute to analyses of both cause‐specific hazard functions, or separate data sources where each individual contributes to the analysis of the cause‐specific hazard function of only a single cause. The approach is modularized into estimation and prediction. For the estimation step, the parameters and the variance‐covariance matrix can be estimated using widely available software. The prediction step utilizes a generic program with plug‐in estimates from the estimation step. The approach is illustrated with three prognostic models for stage IV male oral cancer using different data structures. The first model uses only men with stage IV oral cancer from population‐based registry data. The second model strategically extends the cohort to improve the efficiency of the estimates. The third model improves the accuracy for those with a lower risk of other causes of death, by bringing in an independent data source collected under a complex sampling design with additional other‐cause covariates. These analyses represent novel extensions of existing methodology, broadly applicable for the development of prognostic models capturing both the cancer and noncancer aspects of a patient's health.
机译：本文展示了一种分析离散时间竞争风险数据的一般方法的灵活性，可以容纳复杂的数据结构，不同的原因的不同时间尺度和非标准采样方案。数据可以涉及单个数据源，其中所有个人有助于分析原因特定的危险功能，其中一些个人有助于分析仅一个原因的原因特异性危险功能，而其他个人有助于分析两者原因特定的危险函数，或单独的数据源，其中每个人有助于分析仅单一原因的原因特定的危险功能。该方法是模块化的估计和预测。对于估计步骤，可以使用广泛的可用软件估计参数和方差协方差矩阵。预测步骤利用来自估计步骤的插件估计的通用程序。该方法用不同的数据结构进行了三种预后模型，用于阶段IV阶段雄性口腔癌。第一种模型仅使用来自基于人口的注册数据的IV阶段口腔癌的男性。第二种模型战略性地扩展了群组以提高估计的效率。第三种模型通过带来在复杂的采样设计中收集的独立数据源，提高了其他死亡风险较低的准确度，与其他其他导致协变量在复杂的采样设计中收集。这些分析代表了现有方法的新延长，广泛适用于捕获患者健康癌症和非癌症方面的预后模型的发展。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号