Causal Inference in Multilevel Settings in Which Selection Processes Vary across Schools. CSE Technical Report 708.
Causal Inference in Multilevel Settings in Which Selection Processes Vary across Schools. CSE Technical Report 708.
复制标题
多层次环境中的因果推理，其中选择过程因学校而异。
DOI：
10.1037/e644002011-001
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Michael H. Seltzer
中科院分区：
文献类型：
--
作者：
Junyeop Kim;Michael H. Seltzer
在这份报告中，我们专注于使用倾向评分方法在多地点研究的教育计划和做法的影响，其中治疗和控制条件都制定在每个学校的样本，并分配给治疗是不是随机的。在这种情况下应用倾向评分方法的一个关键挑战是，学生最终接受治疗或控制的过程可能因学校而异。为了帮助捕捉学校之间的选择过程中的差异，并实现在每个学校的治疗和控制学生之间的关键协变量的平衡，我们建议使用多层次逻辑回归模型的倾向得分估计，其中截距和斜率被视为不同的学校。通过分析早期学术推广计划（EAOP）的数据，我们将这种方法的性能与其他可能的估计倾向分数的策略（例如，单水平逻辑回归模型;截距被视为随机，斜率被视为固定的多水平逻辑回归模型）。此外，我们提请注意，未能在每个学校内实现平衡可能会导致误导性的推论，即不同学校之间治疗效果的差异程度，以及有关因素（例如，学校之间的实施差异），这可能会削弱或放大治疗的效果。
In this report we focus on the use of propensity score methodology in multisite studies of the effects of educational programs and practices in which both treatment and control conditions are enacted within each of the schools in a sample, and the assignment to treatment is not random. A key challenge in applying propensity score methodology in such settings is that the process by which students wind up in treatment or control conditions may differ substantially from school to school. To help capture differences in selection processes across schools, and achieve balance on key covariates between treatment and control students in each school, we propose the use of multilevel logistic regression models for propensity score estimation in which intercepts and slopes are treated as varying across schools. Through analyses of the data from the Early Academic Outreach Program (EAOP), we compare the performance of this approach with other possible strategies for estimating propensity scores (e.g., single-level logistic regression models; multilevel logistic regression models with intercepts treated as random and slopes treated as fixed). Furthermore, we draw attention to how the failure to achieve balance within each school can result in misleading inferences concerning the extent to which the effect of a treatment varies across schools, and concerning factors (e.g., differences in implementation across schools) that might dampen or magnify the effects of a treatment.