多水平反应的试验设计及其在大规模教育干预中的应用
Experimental designs for multiple-level responses, with application to a large-scale educational intervention
摘要：
教育研究经常研究自然聚集在教室或学校群体中的主题。当设计一个随机实验来评估针对教师的干预措施，但对教师和学生的影响，功率或预期方差的处理效应需要在两个水平上进行检查。如果处理应用于簇，功率通常会降低。同时，簇设计降低了污染的可能性，并且污染还可以降低检测处理效应的功率。在一个水平上最优的设计对于估计另一个水平上的处理效应可能是无效的。在本文中，我们研究了三种设计的效率和它们检测处理效应的能力：随机化学校处理，随机化学校内的教师处理，完全随机化教师处理。在混合模型框架内对教师和学生水平的三种设计进行了比较，并进行了模拟研究，以比较三种设计的预期治疗方差与簇内和簇间的各种相关性。我们提出了一个计算机程序，研究设计者可以使用它来探索拟议的试验设计和设置下的处理效应的预期方差。
英文摘要：
Educational research often studies subjects that are in naturally clustered groups of classrooms or schools. When designing a randomized experiment to evaluate an intervention directed at teachers, but with effects on teachers and their students, the power or anticipated variance for the treatment effect needs to be examined at both levels. If the treatment is applied to clusters, power is usually reduced. At the same time, a cluster design decreases the probability of contamination, and contamination can also reduce power to detect a treatment effect. Designs that are optimal at one level may be inefficient for estimating the treatment effect at another level. In this paper we study the efficiency of three designs and their ability to detect a treatment effect: randomize schools to treatment, randomize teachers within schools to treatment, and completely randomize teachers to treatment. The three designs are compared for both the teacher and student level within the mixed model framework, and a simulation study is conducted to compare expected treatment variances for the three designs with various levels of correlation within and between clusters. We present a computer program that study designers can use to explore the anticipated variances of treatment effects under proposed experimental designs and settings.
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