首页> 美国卫生研究院文献>BMC Medical Research Methodology >Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study
【2h】

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study

机译:估计常见二元结果的相对风险时稳健的泊松模型和对数二项式模型之间的异常值的鲁棒性比较:模拟研究

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

BackgroundTo estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited.
机译:背景技术为了估计常见二元结果的相对风险或风险比,最流行的基于模型的方法是稳健的(也称为修正的)泊松和对数二项式回归。在这两种方法中,由于对数二项回归基于最大似然,因此认为对数二项式回归可产生更有效的估计量,而健壮的Poisson模型可能不受异常值的影响。与对数二项式模型相比,支持鲁棒泊松模型的鲁棒性的证据非常有限。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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