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Pashley, Nicole E.; Miratrix, Luke W. – Journal of Educational and Behavioral Statistics, 2022
Several branches of the potential outcome causal inference literature have discussed the merits of blocking versus complete randomization. Some have concluded it can never hurt the precision of estimates, and some have concluded it can hurt. In this article, we reconcile these apparently conflicting views, give a more thorough discussion of what…
Descriptors: Research Design, Experimental Groups, Control Groups, Sampling
Peter Z. Schochet – Journal of Educational and Behavioral Statistics, 2025
Random encouragement designs evaluate treatments that aim to increase participation in a program or activity. These randomized controlled trials (RCTs) can also assess the mediated effects of participation itself on longer term outcomes using a complier average causal effect (CACE) estimation framework. This article considers power analysis…
Descriptors: Statistical Analysis, Computation, Causal Models, Research Design
Wendy Chan; Larry Vernon Hedges – Journal of Educational and Behavioral Statistics, 2022
Multisite field experiments using the (generalized) randomized block design that assign treatments to individuals within sites are common in education and the social sciences. Under this design, there are two possible estimands of interest and they differ based on whether sites or blocks have fixed or random effects. When the average treatment…
Descriptors: Research Design, Educational Research, Statistical Analysis, Statistical Inference
Park, Soojin; Esterling, Kevin M. – Journal of Educational and Behavioral Statistics, 2021
The causal mediation literature has developed techniques to assess the sensitivity of an inference to pretreatment confounding, but these techniques are limited to the case of a single mediator. In this article, we extend sensitivity analysis to possible violations of pretreatment confounding in the case of multiple mediators. In particular, we…
Descriptors: Statistical Analysis, Research Design, Influences, Anxiety
Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2022
This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…
Descriptors: Comparative Analysis, Statistical Analysis, Sample Size, Measurement Techniques
Wu, Edward; Gagnon-Bartsch, Johann A. – Journal of Educational and Behavioral Statistics, 2021
In paired experiments, participants are grouped into pairs with similar characteristics, and one observation from each pair is randomly assigned to treatment. The resulting treatment and control groups should be well-balanced; however, there may still be small chance imbalances. Building on work for completely randomized experiments, we propose a…
Descriptors: Experiments, Groups, Research Design, Statistical Analysis
Suk, Youmi; Steiner, Peter M.; Kim, Jee-Seon; Kang, Hyunseung – Journal of Educational and Behavioral Statistics, 2022
Regression discontinuity (RD) designs are commonly used for program evaluation with continuous treatment assignment variables. But in practice, treatment assignment is frequently based on ordinal variables. In this study, we propose an RD design with an ordinal running variable to assess the effects of extended time accommodations (ETA) for…
Descriptors: Regression (Statistics), Program Evaluation, Research Design, English Language Learners