The analysis to possess Shot step 1 try authorized by the Institutional Remark Panel of one’s Medical Faculty out of Leipzig College or university (-ff). Footnote dos
Statistical analyses Research step one
In Sample 1, we started with estimating a CFA based on the responses to the 12 items of the ECR-RD12. We specified two correlated latent factors representing attachment anxiety and avoidance. Cross-loadings and correlations between residuals were fixed to zero. To deal with the ordinal nature of the items, we used the polychoric correlation matrix and robust weighted least squares estimation . To assess model fit, we inspected the comparative fit index (CFI; good fit: > 0.95), the Tucker-Lewis Index (TLI; good fit: > 0.95), the root mean square error of approximation (RMSEA; good fit: < 0.06), and the standardized root mean squared residual (SRMR; good fit: < 0.08; ). Internal consistency of the two scales was evaluated using McDonald's Omega for ordinal items . In case of insufficient fit indices, item reduction was based on modification indices of the CFA as well as content-related considerations. Norm values were computed based on the cumulative percentile distribution of scale scores, stratified for age groups and gender. Analyses were conducted using R version 4.0.3 including the package lavaan (0.6–7; ) as well as IBM SPSS 25.
Efficiency Investigation step one
Model fit of a two-dimensional CFA based on the 12 items of the ECR-RD12 was poor, ? 2 (53) = 8956.1, p < 0.001, CFI = 0.841, TLI = 0.802, RMSEA = 0.263, SRMR = 0.165. Thus, we reduced the item set by subsequently excluding the item involving the highest modification index, each time refitting the model and evaluating model fit. In this way we removed item 6 (due to a cross-loading on anxiety), item 7 (due to a cross-loading on anxiety), and item 1 (due to a cross-loading on avoidance and correlated residuals with item 2). Footnote 3 To establish a measure with the same number of items for each scale, we also omitted item 10 (“I'm afraid that once a romantic partner gets to know me, he or she won't like who I really am.”). This decision was based on content, as the item represents the assumption of not being lovable (see cluster 27 from Fraley et al. ), as compared to the other items of the attachment anxiety subscale (see Table 2, Additional file 1: Table S5).
The reduced 8-item version of the ECR-RD showed good model fit according to the majority of fit indices, ? 2 (19) = 438.1 https://datingranking.net/escort-directory/lansing/, p < 0.001, CFI = 0.989, TLI = 0.983, RMSEA = 0.095, SRMR = 0.044. Standardized factor loadings ranged from 0.77 to 0.91. Model-based internal consistency (McDonald's Omega) was 0.87 for anxiety and 0.91 for avoidance. The correlation between the two latent factors was 0.32. Model parameters can be found in Fig. 1.
Foundation loadings Research step one (N = 2428). Mention Anxiety = ECR-RD8 attachment-relevant anxiety; Cures = ECR-RD8 connection-relevant prevention. Wide variety show standardized prices, residual variances commonly displayed
We computed total (average) scores for the two 4-item scales. Female participants showed slightly higher values on anxiety compared to male participants, t(2426) = 2.11, p < 0.05, d = 0.09, but the sexes did not differ in terms of avoidance, t(2426) = 1.21, p = 0.23. Age was negatively associated with anxiety, r = ? 0.13, p < 0.001, but not significantly associated with avoidance, r = 0.04, p = 0.07. However, when considering non-linear associations between age and attachment styles separately for female and male participants using local regression analyses, we found that young males and old females exhibited especially high scores of avoidance (see Fig. 2). Thus, we computed age- and gender-specific norm values for the two scales (see Additional file 1). Finally, we found that persons who currently live with a partner in the same household report lower values on anxiety, t(2426) = 7.91, p < 0.001, d = 0.32, and avoidance, t(2426) = , p < 0.001, d = 0.90, compared to persons who do not.