According to ecological system theory, both the microsystem environment (home environment) and the more macrolevel environment (provincial environment) influence school engagement in adolescents. This study tests an ecological model of adolescents’ school engagement with 19,084 middle school students across 31 provincial-level regions in China. Multilevel modeling is used to predict adolescents’ school engagement (behavior, emotion, and cognition) at two levels, individual [gender and family socioeconomic status (SES)] and provincial (economy, public cultural facilities, technological industry and education). The school engagement of students varies significantly across provincial-level regions. SES positively affects the school engagement of students. Students benefit from the provincial environment when the economy is booming, public cultural facilities are adequate and education is flourishing. The development of the technology industry fails to boost students’ school engagement. Limitations and future directions are discussed.

The generalized estimating equations (GEE) method has been widely used to analyze longitudinal data since it was proposed by Liang and Zeger (1986). It is well known that the efficiency of the GEE estimator can be seriously affected by the choice of the working correlation matrix. To address the associated misspecification issue, we propose an estimator called mix-GEE based on a finite mixture model for the working correlation. Under mild regularity conditions, the mix-GEE estimator is consistent, asymptotically normal, and asymptotically efficient if data are from a Gaussian mixture model. An important feature of the mix-GEE method is that it guarantees the positive definiteness of the estimated working correlation matrix if either the AR(1) or exchangeable structure is included. It is numerically more stable and displays a better finite sample efficiency than the hybrid GEE method (Leung, Wang, and Zhu (2009)). The value of our method is further demonstrated by simulation studies and data examples.

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Introduction: Previous studies have examined family socioeconomic status (SES) and regional-level factors that predict adolescents' present subjective wellbeing (SWB). However, as adolescents' SWB tends to be future-oriented, this study examined the relationships between family SES and provincial-level economic, educational, and health-related factors and adolescents' present-and future-oriented SWB. Methods: The sample includes 17,341 12-to 17-year-old adolescents (M age = 13.86; SD age = 0.79; 9056 girls and 8285 boys) from 31 different provinces of China. Multilevel modeling was used to analyze the data at two levels. Results: The findings showed that family SES (Level-1) was positively correlated with present life satisfaction (LS-P), present positive affect (PPA), hopeful future expectations (HFE), and positive affect toward future life (FPA), but negatively correlated with present negative affect (PNA) and negative affect toward future life (FNA). Provincial-level (Level-2) years of education per capita, average life expectancy, and human development index (HDI) were positively associated with LS-P, PPA, FPA, and HFE, and negatively associated with PNA; only average life expectancy was negatively associated with FNA. There was no association between gross domestic product (GDP) per capita and SWB. Simple slope analyses demonstrated that, in provinces with relatively less or short years of education per capita, GDP per capita, average life expectancy, or HDI, the correlations between family SES and present-and future-oriented negative affect were stronger. Conclusions: The present-and future-oriented SWB of adolescents from families with low SES in underdeveloped areas was relatively poor. More psychologically focused education activities are needed for these adolescents.

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