Data Analysis

A preliminary examination of the variables was performed. Specifically, the Kolmogorov-Smirnov test was used to assess normality, while Levene’s test was used to assess homoscedasticity. The results of this examination support the application of the parametric tests that were applied in this study. Confirmatory factor analysis (CFA) with the maximum likelihood (ML) estimation was applied to assess the factor structure of the Pandemic Grief Scale. The chi-squared statistic (χ²) was used to assess the sample and the implied covariance matrices; however, this statistic is strongly dependent on the sample size and provides an overly conservative assessment of the model fit. The comparative fit index (CFI) and the goodness-of-fit index (GFI) were used to assess the model fit relative to a baseline model in which all variables are uncorrelated and values above 0.95 indicate good fit, while values above 0.90 are considered to indicate acceptable fit. The root-mean-square error of approximation (RMSEA) was also examined. Ideally, these values should be less than 0.05, but values below 0.08 are considered acceptable (Byrne, 2016; Kline, 2015). Pearson’s r correlation analysis and regression analysis were used to determine the relations between the variables. The mediation model was assessed using Hayes’ Process macro. The significance level was determined at p < .050. The effect size was assessed based on R². Data analysis was conducted in IBM SPSS Statistics 26 and IBM SPSS Amos 26.