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An, Chen; Braun, Henry; Walsh, Mary E. – Educational Measurement: Issues and Practice, 2018
Making causal inferences from a quasi-experiment is difficult. Sensitivity analysis approaches to address hidden selection bias thus have gained popularity. This study serves as an introduction to a simple but practical form of sensitivity analysis using Monte Carlo simulation procedures. We examine estimated treatment effects for a school-based…
Descriptors: Statistical Inference, Intervention, Program Effectiveness, Quasiexperimental Design
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Deke, John; Wei, Thomas; Kautz, Tim – National Center for Education Evaluation and Regional Assistance, 2017
Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…
Descriptors: Intervention, Educational Research, Research Problems, Statistical Bias
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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