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2020-05-21

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/172866

Assessing Consistency of Effects when Applying Multilevel Models to Single-Case Data

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Abstract

In the context of single-case experimental designs, replication is crucial. On the one hand, the replication of the basic effect within a study is necessary for demonstrating experimental control. On the other hand, replication across studies is required for establishing the generality of the intervention effect. Moreover, the "replicability crisis" presents a more general context further emphasizing the need for assessing consistency in replications. In the current text, we focus on replication of effects within a study and we specifically discuss the consistency of effects. Our proposal for assessing the consistency of effects refers to one of the promising data analytical techniques: multilevel models, also known as hierarchical linear models or mixed effects models. One option is to check, for each case in a multiple-baseline design, whether the confidence interval for the individual treatment effect excludes zero. This is relevant for assessing whether the effect is replicated as being non-null. However, we consider that it is more relevant and informative to assess, for each case, whether the confidence interval for the random effects includes zero (i.e., whether the fixed effect estimate is a plausible value for each individual effect). This is relevant for assessing whether the effect is consistent in size, with the additional requirement that the fixed effect itself is different from zero. The proposal for assessing consistency is illustrated with real data and it is implemented in free user-friendly software.

Related resource

https://doi.org/10.3758/s13428-020-01417-0

Subject

Mètodes experimentals, Investigació de cas únic, Models multinivell (Estadística), Disseny d'experiments

Subject (English)

Experimental methods, Single subject research, Multilevel models (Statistics), Experimental design

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Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)

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MANOLOV, Rumen and FERRON, John M. Assessing Consistency of Effects when Applying Multilevel Models to Single-Case Data. Behavior Research Methods. 2020. Vol. 52, num. 6, pags. 2460-2479. ISSN 1554-351X. [consulted: 9 of October of 2026]. Available at: https://hdl.handle.net/2445/172866

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