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Title: Choosing among techniques for quantifying single-case intervention effectiveness
Author: Manolov, Rumen
Solanas Pérez, Antonio
Sierra, Vicenta
Evans, Jonathan J.
Keywords: Investigació de cas únic
Mètode de Montecarlo
Psicologia experimental
Single subject research
Monte Carlo method
Experimental psychology
Issue Date: 2011
Publisher: Elsevier B.V.
Abstract: If single case experimental designs are to be used to establish guidelines for evidence-based interventions in clinical and educational settings, numerical values that reflect treatment effect sizes are required. The present study compares four recently developed procedures for quantifying the magnitude of intervention effect using data with known characteristics. Monte Carlo methods were used to generate AB designs data with potential confounding variables (serial dependence, linear and curvilinear trend, and heteroscedasticity between phases) and two types of treatment effect (level and slope change). The results suggest that data features are important for choosing the appropriate procedure and, thus, inspecting the graphed data visually is a necessary initial stage. In the presence of serial dependence or a change in data variability, the Nonoverlap of All Pairs (NAP) and the Slope and Level Change (SLC) were the only techniques of the four examined that performed adequately. Introducing a data correction step in NAP renders it unaffected by linear trend, as is also the case for the Percentage of Nonoverlapping Corrected Data and SLC. The performance of these techniques indicates that professionals" judgments concerning treatment effectiveness can be readily complemented by both visual and statistical analyses. A flowchart to guide selection of techniques according to the data characteristics identified by visual inspection is provided.
Note: Versió postprint del document publicat a:
It is part of: Behavior Therapy, 2011, vol. 42, num. 3, p. 533-545
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ISSN: 0005-7894
Appears in Collections:Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)

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