Korean Journal of Psychology: General
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- P-ISSN1229-067X
- E-ISSN2734-1127
- KCI
ISSN : 1229-067X
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Vol.41 No.2
Abstract
Mediation models are widely used in various fields such as psychology, education, and business administration. Some traditional methods like Baron and Kenny’s approach and multivariate delta method were used before, but now bootstrap methods have become a standard procedure. Since the bias-corrected bootstrap (BC bootstrap) was proposed to correct for the potential bias in the confidence intervals (CIs) obtained by the percentile bootstrap, the BC method has been frequently used domestically based on some old research that the BC bootstrap provides more accurate CIs and higher power. However, recent studies have reported that the BC method may not be appropriate for testing mediating effects because it produces inflated Type I error rates. The goal of the present study is to enhance researchers’ understanding about testing methods for the mediation effect by examining the recent research trend of testing methods for mediating effects and by comparing the performance of the percentile bootstrap and the BC bootstrap through a series of simulations under various conditions. In Study 1, the results show that the power was high in the order of BC bootstrap, percentile bootstrap, and multivariate delta method. As the number of indicators, the effect size, the factor loading, and the sample size increased, the power also increased. Study 2 demonstrates that Type 1 error rates were also high in the order of BC bootstrap, percentile bootstrap, and multivariate delta method, confirming that the BC bootstrap also generates the highest Type 1 error in structural equation mediation models. Finally, the limitations of this study and guidelines based on the simulation results are discussed.
Abstract
The purpose of this longitudinal study was to examine the psychometric properties of the Korean version of Dimensions of Traumatic Anger Reaction scale-5 (DAR-5-K) over two periods in Korea. For this purpose, an online survey was conducted with 563 Korean adults exposed to traumatic events at time1, and 383 Korean adults exposed to traumatic events at time2. The results were as follows. First, Exploratory Factor Analysis and Confirmatory Factor Analysis supported the one-factor structure, as defined in previous validation studies. Second, the scale showed robust internal consistency and test-retest reliability. Third, DAR-5-K displayed robust concurrent validity and discriminant validity with measures of depression, anxiety, and PTSD symptoms, and also predictive validity with measures of PTSD symptoms. These results suggest that DAR-5-K is an instrument having a brief and satisfactory psychometric properties to measure anger reaction to Korean adults exposed to traumatic events. Implications and recommendations for future research were discussed.
Abstract
This study aimed to extract topics from text big data on the site Jobplanet, and explore the associations between the topics and Job Turnover. Using Latent Semantic Analysis (LSA), 35,031 employee reviews from the top 50 market capitalization organizations were analyzed. After applying a Varimax rotation, 62 topics were finally interpreted and individual topics were grouped into 8 topic groups based on the similarity of their meanings: ‘Autonomy for Hours of Rest’, ‘Growth’, ‘Comparison’, ‘Organizational System’, ‘Organizational Climate’, ‘Pay Satisfaction and Work Intensity’, ‘Perceived Organizational Support’, and ‘Job Characteristics’. As a result of exploring the relationship between each topic and job turnover through Generalized Additive Model (GAM), there were 31 topics showing a linear relationship with turnover, and with 14 topics showing a nonlinear relationship. This study discovered ‘Autonomy for Hours of Rest’ as a concept distinct from other constructs studied in the prior job turnover research. In conclusion, we discussed these findings, limitations, and implications for future research.
Abstract
Item response tree model (IRTree) is a sort of a multidimensional item response theory that incorporates a tree structure depicting a respondent's cognitive response process into item response theory. IRTree has recently received considerable attention from researchers for measuring extreme response style (ERS) that can threaten reliability and factor structure in self-report survey data. In addition to the work of IRTree, we extend IRTree as the mixture item response tree model (MixIRTree), which combines latent class analysis with IRTree for measuring and investigating the possible heterogeneity of data caused by ERS. For analyses, this study used the body symptom and depression scales of the emotional problems in the third wave of KCYPS 2018. The results of the study are as follows. First, the three latent classes were captured, showing the different levels of ERS. The latent class 3 did not show the ERS tendency than the latent classes 1 and 2. The latent class 1 showed the largest ERS tendency. Second, the ERS tendency across the latent classes was different between the negative affect scales. For example, the ERS tendency of the latent class 1 was larger in the depression scale than body symptom scale, while the ERS tendency of the latent class 2 was larger in the body symptom scale than the depression scale. Based on these findings, we provide practical implications of the MixIRTree for measuring the heterogeneity of ERS and discuss the future direction for further study.