Attrition in Randomized Controlled Trials: Using Tracking Information to Correct Bias
分析了四项随机实验中损耗对内部和外部效度的影响，提出利用密集追踪阶段找到的个体信息，通过逆概率加权方法纠正损耗偏差。
This paper analyzes the implications of attrition for the internal and external validity of the results of four randomized experiments and proposes a new method to correct for attrition bias. We find that not including those found during the intensive tracking can lead to a substantial overestimation or underestimation of the intention-to-treat effects, even when attrition without such tracking is balanced. We propose to correct for attrition using inverse probability weighting with estimates of weights that exploit the similarities between missing individuals and those found during an intensive tracking phase.