...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Statistical methods in medical research >Approximate Bayesian Bootstrap procedures to estimate multilevel treatment effects in observational studies with application to type 2 diabetes treatment regimens
【24h】

Approximate Bayesian Bootstrap procedures to estimate multilevel treatment effects in observational studies with application to type 2 diabetes treatment regimens

机译：近似贝叶斯举行程序，以估算多级治疗效果在观察性研究中，应用于2型糖尿病治疗方案

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

Randomized clinical trials are considered as the gold standard for estimating causal effects. Nevertheless, in studies that are aimed at examining adverse effects of interventions, randomized trials are often impractical because of ethical and financial considerations. In observational studies, matching on the generalized propensity scores was proposed as a possible solution to estimate the treatment effects of multiple interventions. However, the derivation of point and interval estimates for these matching procedures can become complex with non-continuous or censored outcomes. We propose a novel Approximate Bayesian Bootstrap algorithm that results in statistically valid point and interval estimates of the treatment effects with categorical outcomes. The procedure relies on the estimated generalized propensity scores and multiply imputes the unobserved potential outcomes for each unit. In addition, we describe a corresponding interpretable sensitivity analysis to examine the unconfoundedness assumption. We apply this approach to examine the cardiovascular safety of common, real-world anti-diabetic treatment regimens for type 2 diabetes mellitus in a large observational database.
机译：随机化的临床试验被认为是估算因果效应的金标准。然而，在旨在检查干预措施的不利影响的研究中，由于道德和财务考虑，随机试验往往是不切实际的。在观察性研究中，提出了在广义倾向评分上的匹配作为估计多种干预措施的治疗效果的可能解决方案。然而，这些匹配程序的点和间隔估计的导出可以与非连续或截取的结果变得复杂。我们提出了一种新颖的近似贝叶斯引导算法，其导致统计上有效的点和间隔估计治疗效果与分类结果。该程序依赖于估计的广义倾向评分，并使每个单位的潜在潜在结果造成差异。此外，我们描述了一种相应的可解释性敏感性分析，以检查未浮动的假设。我们采用这种方法来检查大型观测数据库中2型糖尿病的常见，现实世界抗糖尿病治疗方案的心血管安全性。

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