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Assigning and combining probabilities in single-case studies
Manolov, Rumen; Solanas Pérez, Antonio
Universitat de Barcelona
There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current paper proposes an approach for obtaining further numerical evidence on the importance of the results, complementing the substantive criteria, visual analysis, and primary summary measures. This additional evidence consists of obtaining the statistical significance of the outcome when referred to the corresponding sampling distribution. This sampling distribution is formed by the values of the outcomes (expressed as data nonoverlap, R-squared, etc.) in case the intervention is ineffective. The approach proposed here is intended to offer the outcome"s probability of being as extreme when there is no treatment effect without the need for some assumptions that cannot be checked with guarantees. Following this approach, researchers would compare their outcomes to reference values rather than constructing the sampling distributions themselves. The integration of single-case studies is problematic, when different metrics are used across primary studies and not all raw data are available. Via the approach for assigning p values it is possible to combine the results of similar studies regardless of the primary effect size indicator. The alternatives for combining probabilities are discussed in the context of single-case studies pointing out two potentially useful methods
one based on a weighted average and the other on the binomial test.
Estudi de casos
Investigació de cas únic
Teoremes de límit (Teoria de probabilitats)
Psicologia aplicada
Case studies
Single subject research
Limit theorems (Probability theory)
Applied psychology
(c) American Psychological Association, 2012
American Psychological Association

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