SE_national repr_ECRR&other measures_weighted_mergeRT.sav

The data collection was carried out in a nationally representative online sample by a Hungarian company (Social Research Ltd.). 16,000 members of the company’s research community were invited to participate voluntarily in the research via email. The sample was stratified according to gender, age, education, and settlement type. Following the stratification, the respondents were randomly selected in order to obtain a final, nationally representative sample. There were five age groups (18-29, 30-39, 40-49, and 50-59 years of age, and 60 years of age or older), and three categories of education level (primary and vocational school, secondary, and higher education). The stratification of the sample was completed by adjusting the true proportions of settlement type (capital, cities/towns, and villages) and regions (Central, Eastern, and Western Hungary). The total sample size was N = 993, but the number of respondents to the ECR-R-HU questions was N=958, as the questionnaire was not offered to participants who stated that they had never been in a romantic relationship. After the first, main wave of data collection in December 2018, a second wave was carried out in order to assess the stability of the ECR-R-HU scale. After a 4-month interval in March 2019, the questionnaire was administered again to a smaller subsample (N = 98) of the original sample (Wave 2 data). In addition to socio-demographic questions and the ECR-R-HU, participants were given the Hungarian version of the following four questionnaires in order to test the convergent validity of the ECR-R-HU: 1. WHO Well-being Questionnaire (WBI-5), 2. Perceived Stress Scale – 4 (PSS-4), 3. Depression Scale Questionnaire<br> (DS1K), 4. Family Assessment Device (FAD). ECR-R-HU item distributions were checked by Kolmogorov-Smirnov tests. To test the original two-factor model of the ECR-R, a series of Confirmatory Factor Analyses (CFAs) were conducted on AMOS 21.0. Maximum likelihood estimations were used and four model fit indices were examined: the Chi Square Test of Model Fit (χ²/df ratio, which indicates a good model fit below 3), the Steiger-Lind Root Mean Square Error of Approximation (RMSEA which indicates a good model fit below .05), the Tucker-Lewis Index (TLI which signifies a good fit above .95), and the Bentler Comparative Fit Index (CFI which indicates a good fit above .95). RMSEA between .05 and .10, CFI and TLI between .90 and .95 mean a moderate fit. Exploratory Factor Analyses (EFAs) were conducted using Principal Axis Factoring (PAF) method with varimax rotation to examine the orthogonal structure of the latent factors in our study. We also used Hierarchical Cluster Analysis (HCA) to confirm the latent structure of the items based on their similarities. Between-groups linkage method was used, and the items’ distances/similarities were examined with Pearson correlations. The internal consistency of the subscales was measured by calculating Cronbach’s alphas. Descriptive statistics showed that the distribution of the ECR-R-HU subscale scores did not follow a normal distribution, so we used non-parametric statistical tests (Spearman correlations, Mann-Whitney Test, Kruskal-Wallis Test) for further analyses. The research was approved by the Research Ethics Committee of Semmelweis University Budapest, Hungary. The license number: RKEB: 197/2018.