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López Nicolás, Rubén

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López Nicolás, Rubén
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Universidad de Murcia. Departamento de Tecnología de los Alimentos,Nutrición y Bromatología
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    Reliability Generalization of the School Attitude Assessment Survey‑Revised: A Meta‑Analytic Structural Equation Modeling Approach
    (Sage Publications, 2025-06-09) López López, José Antonio; López Nicolás, Rubén; Sandoval Lentisco, Alejandro; Sánchez Meca, Julio; Veas Iniesta, Alejandro; Psicología Evolutiva y de la Educación; Facultad de Psicología y Logopedia
    The School Attitude Assessment Survey-Revised (SAAS-R) is a popular scale for assessing attitudinal and motivational aspects of students’ academic achievement. However, evidence on key psychometric properties of the SAAS-R such as reliability remains limited. We conducted a reliability generalization study of the SAAS-R using meta-analytic structural equation modeling (MASEM). We included studies reporting an application of the SAAS-R and providing correlation coefficients between the SAAS-R subscales. We searched ERIC, PsycINFO, Academic Search Premier, Supplemental Index, and Web of Science from database inception to July 2023. Analyses were based on 18 independent matrices from 13 studies examining 8712 participants. Our main results, based on a one-stage, correlation-based MASEM approach and with omega total as the reliability measure, yielded an overall reliability estimate of 0.795 (95% CI 0.778–0.811). This suggests that the SAAS-R offers good score reliability for research and practice purposes. Applications using adapted versions obtained on average higher score reliabilities than the original ones. We discuss the implications of these results, which need to be interpreted with caution given the important reporting limitations of the primary studies included.
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    Open Access
    Reliability generalization meta‑analysis: comparing different statistical methods
    (Springer, 2024-01-22) López‑Ibáñez, Carmen; López Nicolás, Rubén; Blázquez‑Rincón, Desirée M.; Sánchez Meca, Julio; Psicología Básica y Metodología; Facultad de Psicología y Logopedia
    Reliability generalization (RG) is a kind of meta-analysis that aims to characterize how reliability varies from one test application to the next. A wide variety of statistical methods have typically been applied in RG meta-analyses, regarding statistical model (ordinary least squares, fixed-effect, random effects, varying-coefficient models), weighting scheme (inverse variance, sample size, not weighting), and transformation method (raw, Fisher’s Z, Hakstian and Whalen’s and Bonett’s transformation) of reliability coefficients. This variety of methods compromise the comparability of RG meta-analyses results and their reproducibility. With the purpose of examining the influence of the different statistical methods applied, a methodological review was conducted on 138 published RG meta-analyses of psychological tests, amounting to a total of 4,350 internal consistency coefficients. Among all combinations of procedures that made theoretical sense, we compared thirteen strategies for calculating the average coefficient, eighteen for calculating the confidence intervals of the average coefficient and calculated the heterogeneity indices for the different transformations of the coefficients. Our findings showed that transformation methods of the reliability coefficients improved the normality adjustment of the coefficient distribution. Regarding the average reliability coefficient and the width of confidence intervals, clear differences among methods were found. The largest discrepancies were found between the different strategies for calculating confidence intervals. Our findings point towards the need for the meta-analyst to justify the statistical model assumed, as well as the transformation method of the reliability coefficients and the weighting scheme.
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    Open Access
    A reliability generalization meta-analysis of the dimensional obsessive-compulsive scale
    (2021-02) Rubén López-Nicolás; María Rubio-Aparicio; Carmen López-Ibáñez; Julio Sánchez-Meca; López Nicolás, Rubén; Rubio Aparicio, María; López-Ibáñez, Carmen; Sánchez Meca, Julio; Psicología Básica y Metodología
    Background: The Dimensional Obsessive-Compulsive Scale (DOCS) is a well-established tool for assessing obsessive-compulsive symptomatology. A reliability generalization meta-analysis was conducted to estimate the average reliability of DOCS scores and how reliability estimates vary according to the composition and variability of samples, to identify study characteristics that can explain its variability, and to estimate the reliability induction rate. Method: A literature search produced 86 studies that met the inclusion criteria. Results: For the DOCS total scores, an average alpha coefficient of .925 was found (95% CI [.920,.931]), as well as mean alphas of .881, .905, .913, and .914 for Contamination, Responsibility, Unacceptable Thoughts, and Symmetry subscales, respectively. Moderator analysis showed that internal consistency fell signifi cantly the more clinical and subclinical participants there were in the sample, and the larger the mean score in the sample for the total scores. The most important moderator variables for the subscales were the standard deviation and the mean of the scores. Conclusions: The DOCS scores exhibited excellent internal consistency reliability for both total score and subscale scores and DOCS is suitable both for research and clinical purposes.
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    Open Access
    Reproducibility of Published Meta-Analyses on Clinical-Psychological Interventions
    (SAGE Publications, 2024-02-05) López Nicolás, Rubén; Lakens, Daniel; López López, José Antonio; Rubio Aparicio, María; Sandoval Lentisco, Alejandro; López-Ibáñez, Carmen; Blázquez-Rincón, Desirée; Sánchez Meca, Julio; Psicología Básica y Metodología; Facultad de Psicología y Logopedia
    Meta-analysis is one of the most useful research approaches, the relevance of which relies on its credibility. Reproducibility of scientific results could be considered as the minimal threshold of this credibility. We assessed the reproducibility of a sample of meta-analyses published between 2000 and 2020. From a random sample of 100 articles reporting results of meta-analyses of interventions in clinical psychology, 217 meta-analyses were selected. We first tried to retrieve the original data by recovering a data file, recoding the data from document files, or requesting it from original authors. Second, through a multistage workflow, we tried to reproduce the main results of each meta-analysis. The original data were retrieved for 67% (146/217) of meta-analyses. Although this rate showed an improvement over the years, in only 5% of these cases was it possible to retrieve a data file ready for reuse. Of these 146, 52 showed a discrepancy larger than 5% in the main results in the first stage. For 10 meta-analyses, this discrepancy was solved after fixing a coding error of our data-retrieval process, and for 15 of them, it was considered approximately reproduced in a qualitative assessment. In the remaining meta-analyses (18%, 27/146), different issues were identified in an in-depth review, such as reporting inconsistencies, lack of data, or transcription errors. Nevertheless, the numerical discrepancies were mostly minor and had little or no impact on the conclusions. Overall, one of the biggest threats to the reproducibility of meta-analysis is related to data availability and current data-sharing practices in meta-analysis.
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