This study explores the use of state data sets and meta-analysis of low-powered studies to evaluate a school-based dropout prevention program for students with disabilities. The program was implemented in several states. A randomized controlled trial was infeasible because schools were not chosen at random; furthermore, pretest data were minimal. The use of extant state data allowed these obstacles to be overcome by providing valid pre- and post-intervention outcomes as well as a large selection of schools and variables to create reasonable matches for the treatment schools. Results from four states were synthesized meta-analytically to evaluate whether the program had a significant impact on any of seven proximal and distal outcome variables. No such impacts were demonstrated. More importantly, this paper demonstrates and explains the methodological steps and choices involved in a quasi-experimental evaluation approach that may be applied to cases for which large amounts of extant data are available.

这项研究探索了使用状态数据集和低能级研究的荟萃分析来评估针对残疾学生的基于学校的辍学预防计划。该计划已在多个州实施。随机对照试验是不可行的，因为学校不是随机选择的。此外，预测试数据很少。现有状态数据的使用通过提供有效的干预前后，以及大量选择的学校和变量来为治疗学校创造合理的匹配，从而克服了这些障碍。通过荟萃分析综合了来自四个州的结果，以评估该程序是否对七个近端和远端结果变量中的任何一个产生了显着影响。没有显示出这种影响。更重要的是，