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85; Di selleck chemical Fabio and Palazzeschi, 2011). Data analysis Factor analysis was used to identify attachment dimensions, with the objective of assessing the validity of the hypothesized construct (WRC). A series of exploratory factor analyses (EFAs) together with maximum likelihood (ML) analyses were conducted to verify the factor structure of the WRC. As suggested in most of the relevant literature, the number of components extracted was based on the percentage of variance accounted for, the Kaiser-Guttman method, and the scree plot (Nunnally and Bernstein, 1994; Giannini et al., 2014). We then performed a confirmatory factor analysis (CFA), and, to evaluate the model's goodness of fit, a number of indexes were used. Since the chi-square fit index depends on sample size (Schermelleh-Engel et al., 2003), two relative fit indexes were considered because they can generally be used in large as well as small samples: the TLI (Tucker-Lewis Index) and the CFI (Comparative Fit Index; Bentler, 1990). Values of these indexes higher than 0.90 indicate satisfactory fit. In addition, the SRMR (Standardized Root Mean Square Residual) and the RMSEA (Root Mean Square Error of Approximation) were used because they are currently two of the most popular measures of model fit and provide fundamental indications of how well a proposed theory fits the data (Hooper et al., 2008; Giannini et al., 2011; Craparo et al., 2015; Di Fabio and Gori, 2015; Gori et al., 2015). Reliability for each scale was calculated using Cronbach's alpha coefficient I-BET-762 mw (Cronbach, 1951), several aspects of concurrent validity were verified using Pearson's r coefficient, and statistical analyses were conducted using SPSS 18.0 and AMOS Fluvoxamine 6.0. Results Construct validity Examination of the scree plot (Cattell, 1966), the percentage of variance accounted for, and the structure matrix (Horn, 1965; Zwick and Velicer, 1986; Glorfeld, 1995) indicated that as many as three factors should be retained for rotation. The results of the exploratory factor analysis (EFA) (Promax rotation) showed a factor structure with three principal dimensions for both Part A and Part B of the WRC construct. So, on the basis of the factor analysis criteria, we extracted three factors accounting for 60.44% of the total variance for Part A (eigen-values > 1; 5.26, 1.51, 1,10), and, likewise, we extracted three factors accounting for 71.22% of the total variance for Part B (eigen-values > 1; 6.74, 1.37, 1.15). The factor structure matrix shows the three independent and specular factors of the two parts of the WRC construct (see Table ?Table11). Table 1 Factor structure matrix for the two parts of WRC. In order to verify the factor structure, we performed a confirmatory factor analysis (CFA) on the basis of the EFA results that indicated three main factors. The goodness-of-fit indexes showed an excellent fit of the model to the data for Part A (see Table ?Table2).2). As regards Part B, although the chi-square was significant (p
