2022
DOI: 10.1002/pits.22812
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Psychometric properties of the Greek translation of the Friendship Quality Questionnaire

Abstract: The present study examines the psychometric properties of the long form (LF) of the Greek translation of the Friendship Quality Questionnaire (FQQ), a widely recognized self‐report instrument that assesses children's perceptions of the qualities of their friendships. Four hundred seventeen (417) typically developing primary‐school students (50.8% boys), aged between 8 and 12 years (M = 9.77 years old, SD = 1.2), who had a mutual best friend in their class, completed the survey at school. Confirmatory factor an… Show more

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Cited by 2 publications
(3 citation statements)
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“…These authors demonstrate that AVE is highly sensitive to models with high factor loadings and high factor loadings heterogeneity (i.e., high standard deviation of average factor loadings), while CR is sensitive to models with more than 10 items. The commonly accepted thresholds for CR (i.e., ≥0.70) and AVE (i.e., ≥0.50) were therefore adjusted accordingly, and analyzed in conjunction with the standard error of measurement (SEM < SD/2; e.g., Kouvava et al, 2022). Cronbach's alpha and McDonald's omega coefficients, as well as correlations between the FRTA + R factors were also observed.…”
Section: Discussionmentioning
confidence: 99%
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“…These authors demonstrate that AVE is highly sensitive to models with high factor loadings and high factor loadings heterogeneity (i.e., high standard deviation of average factor loadings), while CR is sensitive to models with more than 10 items. The commonly accepted thresholds for CR (i.e., ≥0.70) and AVE (i.e., ≥0.50) were therefore adjusted accordingly, and analyzed in conjunction with the standard error of measurement (SEM < SD/2; e.g., Kouvava et al, 2022). Cronbach's alpha and McDonald's omega coefficients, as well as correlations between the FRTA + R factors were also observed.…”
Section: Discussionmentioning
confidence: 99%
“…Another aim is to test the factorial invariance of the scale across gender and grade levels in order to compare latent means. Latent mean comparison analysis is more powerful and outperforms traditional techniques of comparison by providing more accurate results and less biased mean estimations (Chen et al, 2019;Kouvava et al, 2022). Grade level was preferred to age since Mascret et al (2021) had found no significant results for the predictive role of age in a large sample of French students.…”
Section: Introductionmentioning
confidence: 99%
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