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Psicothema was founded in Asturias (northern Spain) in 1989, and is published jointly by the Psychology Faculty of the University of Oviedo and the Psychological Association of the Principality of Asturias (Colegio Oficial de Psicólogos del Principado de Asturias).
We currently publish four issues per year, which accounts for some 100 articles annually. We admit work from both the basic and applied research fields, and from all areas of Psychology, all manuscripts being anonymously reviewed prior to publication.

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Change in the center of the distribution and in the individual scores: Relation with heteroskedastic pre- and post-test distributions

Eduardo Estrada1, José Manuel Caperos2,3, and Antonio Pardo1

1 Universidad Autónoma de Madrid and
2 Fundación San Juan de Dios, and
3 Universidad Pontificia de Comillas

Background: Although average-based effect size (ES) and percentage of individual changes (PIC) are quite different, they are not independent: larger ESs lead to higher PICs. However, this association has not been sufficiently explored. Method: We analyzed this association based on data simulated in the context of a pre-post design, with and without control groups. We simulated various distributions, sample sizes, degrees of test-retest reliability, effect sizes, and different variances in pre- and post-test. Results: The PIC is closely associated with the ES across a wide variety of empirically frequent scenarios. In the “single group pre-post designs”, the linear regression model shows R2 values above 0.90. In the “control group pre-post designs”, the linear regression model shows R2 values above 0.80. These results were found even when the post-test variability differed from that of the pre-test, replicating, extending and generalizing the findings in previous studies. Conclusions: (1) In the absence of information about the PIC, the ES may be used to estimate this percentage. (2) The PIC is useful in interpreting the meaning of ES measures.

Cambio en el centro de la distribución y en las puntuaciones individuales: relación con distribuciones heteroscedasticas pre y post prueba. Antecedentes: aunque el tamaño del efecto (ES) y el porcentaje de cambios individuales (PIC) son cosas distintas, no parecen ser independientes: mayores ESs conllevan mayores PICs. Pero esta relación todavía no ha sido suficientemente explorada. Método: estudiamos dicha relación mediante datos simulados en el contexto de un diseño pre-post con y sin grupo control. En la simulación se han utilizado diferentes distribuciones, tamaños muestrales, niveles de fiabilidad test-retest, efectos de varios tamaños y distintas variabilidades en el pre- y en el post-test. Resultados: el PIC está estrechamente relacionado con el ES. En los diseños pre-post, el modelo de regresión lineal ofrece valores R2 por encima de 0,90. En los diseños pre-post con grupo control, valores R2 por encima de 0,80. Estos resultados se mantienen incluso cuando la variabilidad del post-test es distinta de la del pre-test. Conclusiones: (1) cuando no se tiene información sobre el PIC, el tamaño del efecto puede utilizarse para estimar ese porcentaje; (2) el PIC sirve para precisar el significado de las medidas del tamaño del efecto.

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Impact factor 2022:  JCR WOS 2022:  FI = 3.6 (Q2);  JCI = 1.21 (Q1) / SCOPUS 2022:  SJR = 1.097;  CiteScore = 6.4 (Q1)