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Baek, Eunkyeng; Luo, Wen; Henri, Maria – Journal of Experimental Education, 2022
It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Comparative Analysis, Statistical Inference
Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Cimpian, Joseph R. – Journal of Research on Educational Effectiveness, 2017
A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…
Descriptors: Regression (Statistics), Intervention, Quasiexperimental Design, Simulation
Ugille, Maaike; Moeyaert, Mariola; Beretvas, S. Natasha; Ferron, John M.; Van den Noortgate, Wim – Journal of Experimental Education, 2014
A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect…
Descriptors: Effect Size, Statistical Bias, Sample Size, Regression (Statistics)
Porter, Kristin E.; Reardon, Sean F.; Unlu, Fatih; Bloom, Howard S.; Robinson-Cimpian, Joseph P. – MDRC, 2014
A valuable extension of the single-rating regression discontinuity design (RDD) is a multiple-rating RDD (MRRDD). To date, four main methods have been used to estimate average treatment effects at the multiple treatment frontiers of an MRRDD: the "surface" method, the "frontier" method, the "binding-score" method, and…
Descriptors: Regression (Statistics), Research Design, Quasiexperimental Design, Research Methodology
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
Jo, Booil; Asparouhov, Tihomir; Muthen, Bengt O.; Ialongo, Nicholas S.; Brown, C. Hendricks – Psychological Methods, 2008
Cluster randomized trials (CRTs) have been widely used in field experiments treating a cluster of individuals as the unit of randomization. This study focused particularly on situations where CRTs are accompanied by a common complication, namely, treatment noncompliance or, more generally, intervention nonadherence. In CRTs, compliance may be…
Descriptors: Individual Characteristics, Intervention, Statistical Inference, Inferences