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  1. 1

    Testing misspecifications in structural equation modeling by Dominguez-Lara, Sergio, Merino-Soto, César

    Published 2018
    “…In this sense, modification indices provide useful information about additional specifications that could be done to improve model fit. …”
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  2. 2

    Best Practices in the Use of Bifactor Models: Conceptual Grounds, Fit Indices and Complementary Indicators by Flores-Kanter, Pablo Ezequiel, Dominguez-Lara, Sergio, Trógolo, Mario Alberto, Medrano, Leonardo Adrián

    Published 2018
    “…To address this problem, several researchers have proposed multiple criteria to assess bifactor models, such as a) conceptual grounds, b) overall model fit indices, and c) specific bifactor model indicators. In this article, we provide a brief summary of these criteria. An example using data gathered from a recently published research article is also provided to show how taking into account all criteria, rather than solely SEM model fit indices, may prevent researchers from drawing wrong conclusions.…”
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  3. 3

    Review of Methodologies Used in Factorial Studies of Ryff’s Psychological Wellbeing Scales (Spanish Version) by Dominguez-Lara, Sergio, Navarro-Loli, Jhonatan Steeven

    Published 2018
    “…A direct search of digital databases for instrumental studies that analyze the PWBS-E identified nine papers providing relevant information. As for studies using confirmatory factor analysis, differences regarding software and estimation methods were observed, but the majority of them does not indicate which type of correlation matrix was used. …”
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  4. 4

    Psychometric analysis of a purposeful delay scale in Peruvian college students by Dominguez-Lara, Sergio, Rodríguez- Sullca, Fiorela, Moreta-Herrera, Rodrigo

    Published 2022
    “…Furthermore, the bivariate association between the dimensions of the construct and the measures of academic burnout, depression and anxiety was significant (r> .20), although a subsequent hierarchical regression indicated that it only provides a significant variation to academic burnout (ΔR2> .10). …”
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