Poster #6 - Impacts of Measurement Error in Pretest on Treatment Effect Estimate in Pretest-and-Posttest Design Analysis

• In Event: 47.099 - MTCC Poster Session 11
  In Poster Session: 47.099-1 - Division D Section 2 Statistical Theory and Quantitative Methodologies

Abstract

In program evaluation, evaluating the treatment effect accurately is of most importance. In order to achieve the goal, random assignment is desirable, but in reality the randomization can be imperfect, in which case preexisting difference will exist between treatment conditions. Furthermore, there always will be measurement errors in pretest. These two factors can create serious challenges for evaluators to accurately gauge the treatment effect and the impacts of these factors are not well known. Thus, in this paper, we addressed how much bias occurs in estimating treatment effect when the random assignment is imperfect and when there is a measurement error in pretest in evaluation studies that use the pretest-and-posttest design.

Authors

• Yasuo Miyazaki, Virginia Polytechnic Institute and State University

• Akihito Kamata, Southern Methodist University

• Kazuaki Uekawa, ICF International