论文标题
营养流行病学的测量误差：调查
Measurement Error in Nutritional Epidemiology: A Survey
论文作者
论文摘要
本文回顾了营养流行病学领域中暴露变量的测量误差的偏差校正模型。测量误差通常会减弱估计的斜率向零。由于测量误差的影响，参数估计的推断是保守的，斜率参数的置信区间太窄。估计量和置信区间的偏差纠正是主要兴趣的。我们回顾以下偏差校正模型：回归校准方法，基于可能性的模型，缺少数据模型，基于仿真的方法，非参数模型和基于采样的程序。
This article reviews bias-correction models for measurement error of exposure variables in the field of nutritional epidemiology. Measurement error usually attenuates estimated slope towards zero. Due to the influence of measurement error, inference of parameter estimate is conservative and confidence interval of the slope parameter is too narrow. Bias-correction in estimators and confidence intervals are of primary interest. We review the following bias-correction models: regression calibration methods, likelihood based models, missing data models, simulation based methods, nonparametric models and sampling based procedures.
