Latent variable models for analyzing children's processing ability

In this paper, we develop a latent processing ability model to analyze the speed of processing ability data. Our approach can not only effectively evaluate the effects of covariates on the latent processing ability, but also estimate the latent trait of each child by calculating its posterior mean. In addition, we derive the correlations structure of latent traits among different age groups. Simulations are conducted to evaluate the performance of our proposed model. The results indicated that the estimation of model parameters is satisfactory overall. The method is evaluated using real data from children aged 4–7 years in Changchun, China.     

Moderation Analysis Using a Two-Level Regression Model

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.     

Development and validation of a Christian-based Grief Recovery Scale

The purpose of this study was to develop and validate a Christian-based Grief Recovery Scale (CGRS) which was used to measure Christians recovering from grief after a significant loss. Taiwanese Christian participants were recruited from churches and a comprehensive university in northern Taiwan. They were affected by both the Christian faith and Chinese cultural beliefs. The CGRS is developed through replicated factor analyses in three stages. The final version of the CGRS retains 35 Likert-type items and consists of six factors: spiritual well-being; recovering meaning and sense of control; ongoing physical and emotional responses; reassuring faith; strongly missing a deceased loved one; and life disturbance. The evidence for CGRS reliability and validity is highlighted. Implications for research and counselling practice are suggested.     

Effects of Three Sources of Social Support on Survivors' Posttraumatic Stress After the Wenchuan Earthquake

This study investigated the relationship between social support and symptoms of posttraumatic stress among adolescents who were exposed to the 2008 Wenchuan earthquake in China. The results showed that three sources of social support—support from family, support from friends, and support from significant others—have significant main effects on posttraumatic stress disorder (PTSD). Buffering effects of social support were not supported. Gender and residency were also associated with PTSD, with female adolescents and adolescents from rural areas demonstrating higher levels of PTSD than their male counterparts and adolescents from urban and township areas.     

Magnetic-field dependence of nucleation undercoolings in non-magnetic metallic melts

The nucleation undercoolings of non-magnetic metals like paramagnetic aluminium in high magnetic fields were measured by the differential thermal analysis technique. It was shown that the nucleation undercooling of pure aluminium increased with increasing the magnetic field, while its melting temperature was hardly changed. Based on the model of magnetic dipoles at the interface, it is proposed that the magnetic-field-induced interfacial energy mainly contributes to the increase in undercooling. The change in undercooling in the magnetic field is calculated theoretically, which is in comparison with experimental data. Additionally, the inhibition of atom diffusion in the magnetic field plays a role in the change of undercooling.     

Comparing Latent Means Without Mean Structure Models: A Projection-Based Approach

The conventional setup for multi-group structural equation modeling requires a stringent condition of cross-group equality of intercepts before mean comparison with latent variables can be conducted. This article proposes a new setup that allows mean comparison without the need to estimate any mean structural model. By projecting the observed sample means onto the space of the common scores and the space orthogonal to that of the common scores, the new setup allows identifying and estimating the means of the common and specific factors, although, without replicate measures, variances of specific factors cannot be distinguished from those of measurement errors. Under the new setup, testing cross-group mean differences of the common scores is done independently from that of the specific factors. Such independent testing eliminates the requirement for cross-group equality of intercepts by the conventional setup in order to test cross-group equality of means of latent variables using chi-square-difference statistics. The most appealing piece of the new setup is a validity index for mean differences, defined as the percentage of the sum of the squared observed mean differences that is due to that of the mean differences of the common scores. By analyzing real data with two groups, the new setup is shown to offer more information than what is obtained under the conventional setup.     

Robust Methods for Moderation Analysis with a Two-Level Regression Model

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.     

Individual-based relative deprivation (IRD) decreases prosocial behaviors

Five studies investigated the relationship between individual-based relative deprivation (IRD) and prosocial behaviors. Study 1 found that income satisfaction, a concept closely related to IRD, was negatively associated with prosocial values across cultures. Study 2 found a negative association between IRD and prosocial aspirations among a sample of Chinese university students. Study 3 revealed a negative association between IRD and volunteer behaviors. In Studies 4 and 5, we found that laboratory-induced IRD decreased undergraduate students’ prosocial values and behaviors. Moreover, Study 5 also found that the tendency to prioritize self-interest over others’ mediated the effect of IRD on prosocial behaviors. Implications of these findings are discussed.     

Determinants of pro‐environmental consumption intention in rural China: The role of traditional cultures,personal attitudes and reference groups

This study aimed to identify social‐psychological predictors of pro‐environmental consumption intention in rural China. To this end, a proposed conceptual model was tested by analyzing the survey data derived from 972 rural respondents in Jiangxi province in south‐eastern China. Results showed that the endorsement of traditional cultures (man–nature orientation and collectivism) was linked with pro‐environmental consumption behaviuor, but was mediated by intentions. Personal attitudes (environmental cognition and environmental affect) and reference groups influenced both intention and behaviour. The results also provided good evidence of the intention–behaviour relationship. These findings provided a better understanding of the process in which Chinese rural residents developed their pro‐environmental consumption behaviours.     

Priming modernity and work experiences strengthens the association between fairness/harm concerns and anger in China

According to the CAD model of emotional responses to immorality, if an event violates the moral foundations of justice and harm, people will feel angry. However, the model is silent on whether the strength of association between anger and perceived injustice/harm is context‐dependent. Using a contextual priming paradigm, the current research shows that in China, the association between anger and perceived injustice/harm is stronger when work (vs family) and modern (vs traditional) contexts are primed. Specifically, we primed modernity versus traditionality (Experiment 1) and work experiences (Experiment 2) and measured the strength of association between justice/harm concerns and anger. The results show that: (i) the linkage between justice/harm concern and anger was stronger in the modernity priming condition than in the tradition priming or control conditions; and (ii) the linkage between justice/harm concern and anger was stronger in the work experience priming condition than in the control condition. In short, priming modern and work contexts strengthens the association between justice/harm concerns and anger, suggesting the strength of the morality–emotion link is context‐dependent.