Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study

Autor/inn/en	Heyvaert, Mieke; Moeyaert, Mariola; Verkempynck, Paul; Van den Noortgate, Wim; Vervloet, Marlies; Ugille, Maaike; Onghena, Patrick
Titel	Testing the Intervention Effect in Single-Case Experiments: A Monte Carlo Simulation Study
Quelle	In: Journal of Experimental Education, 85 (2017) 2, S.175-196 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0973
DOI	10.1080/00220973.2015.1123667
Schlagwörter	Monte Carlo Methods; Simulation; Intervention; Replication (Evaluation); Randomized Controlled Trials; Incidence; Hierarchical Linear Modeling; Research Design; Error Patterns; Testing; Least Squares Statistics; Regression (Statistics) + Suchen Sie Ihr Suchwort? Monte-Carlo-Methode; Simulation program; Simulationsprogramm; Vorkommen; Forschungsdesign; Fehlertyp; Testdurchführung; Testen; Regression; Regressionsanalyse
Abstract	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, number of cases included in a study, number of measurement occasions for each case, and between-case variance. Under the simulated conditions, Type I error rate was under control at the nominal 5% level for both HLM and RTcombiP. Furthermore, for both procedures, a larger number of combined cases resulted in higher statistical power, with many realistic conditions reaching statistical power of 80% or higher. Smaller values for the between-case variance resulted in higher power for HLM. A larger number of data points resulted in higher power for RTcombiP. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01