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Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick – Journal of Experimental Education, 2017
This article reports on a Monte Carlo simulation study, evaluating two approaches for testing the intervention effect in replicated randomized AB designs: two-level hierarchical linear modeling (HLM) and using the additive method to combine randomization test "p" values (RTcombiP). Four factors were manipulated: mean intervention effect,…
Descriptors: Monte Carlo Methods, Simulation, Intervention, Replication (Evaluation)
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Manolov, Rumen; Solanas, Antonio; Bulte, Isis; Onghena, Patrick – Journal of Experimental Education, 2010
This study deals with the statistical properties of a randomization test applied to an ABAB design in cases where the desirable random assignment of the points of change in phase is not possible. To obtain information about each possible data division, the authors carried out a conditional Monte Carlo simulation with 100,000 samples for each…
Descriptors: Monte Carlo Methods, Effect Size, Simulation, Evaluation Methods
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Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2009
The sample size determination is an important issue for planning research. However, limitations in size have seldom been discussed in the literature. Thus, how to allocate participants into different treatment groups to achieve the desired power is a practical issue that still needs to be addressed when one group size is fixed. The authors focused…
Descriptors: Sample Size, Research Methodology, Evaluation Methods, Simulation