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Diane Marcotte Thierno M. O. Diallo Marie-Laurence Paré 《European Journal of Psychology of Education - EJPE》2018,33(4):727-748
Many studies have reported an increase in mental health problems during post-secondary transition, often originating from high school years. The present study examined how depressive symptoms during the 2 years following the post-secondary transition could be predicted by, on the one hand, school performance, externalized and learning difficulties, and depressive symptoms before the post-secondary transition, and on the other hand, personal factors, family functioning, and adjustment to college after the transition. From a sample of 438 participants (M = 16.20, SD = 0.87) at time point 1, an integrated model was elaborated using structural equation modeling. The statistical analyses showed that the five constructs fit the data well. The path coefficients showed a negative relationship between externalized and learning problems as perceived by the teacher (ELPT) before the transition and academic performance (AP). Personal characteristics (PC) negatively predicted academic adjustment (AC) over time, whereas the path coefficients between the family factor (FF) and AC were not significant over time. ELPT and AP negatively predicted depression at time point 1. At time points 2 and 3, PC positively predicted depression, and depressive symptoms were positively related over time. The percentage of variance accounted for by the depressive symptoms increased over time. 相似文献
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Jiesi Guo Herbert W. Marsh Philip D. Parker Theresa Dicke Oliver Lüdtke Thierno M. O. Diallo 《Structural equation modeling》2019,26(4):529-556
In this study, we contrast two competing approaches, not previously compared, that balance the rigor of CFA/SEM with the flexibility to fit realistically complex data. Exploratory SEM (ESEM) is claimed to provide an optimal compromise between EFA and CFA/SEM. Alternatively, a family of three Bayesian SEMs (BSEMs) replace fixed-zero estimates with informative, small-variance priors for different subsets of parameters: cross-loadings (CL), residual covariances (RC), or CLs and RCs (CLRC). In Study 1, using three simulation studies, results showed that (1) BSEM-CL performed more closely to ESEM; (2) BSEM-CLRC did not provide more accurate model estimation compared with BSEM-CL; (3) BSEM-RC provided unstable estimation; and (4) different specifications of targeted values in ESEM and informative priors in BSEM have significant impacts on model estimation. The real data analysis (Study 2) showed that the differences in estimation between different models were largely consistent with those in Study1 but somewhat smaller. 相似文献
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This series of simulation studies evaluate, in the context of applied research settings, the impact of the parameterization of the covariance structure of the growth mixture model (GMM) on the regression coefficient and standard error estimates in the 3-step method. The results show that the 1-step approach performs better than the 3-step method across the simulation studies. However, the performance of the 3-step method depends slightly or importantly on the parameterization of the GGM from the first step, on the inclusion or not of the predictor at the first step of the analysis, on the population model, and on the type (i.e., logit vs. linear) and size of the regression coefficient estimates. 相似文献
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Laurier Fortin Diane Marcotte Thierno Diallo Pierre Potvin Égide Royer 《European Journal of Psychology of Education - EJPE》2013,28(2):563-583
This study tests an empirical multidimensional model of school dropout, using data collected in the first year of an 8-year longitudinal study, with first year high school students aged 12–13 years. Structural equation modeling analyses show that five personal, family, and school latent factors together contribute to school dropout identified at 19 years of age: poor parent–teenager relationships, youth depression and family difficulties, negative classroom climate, negative school interactions, and poor academic achievement. This model increases our understanding of the dropout process in the general population and has direct implications for the development of high school dropout prevention programs. 相似文献
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John Ulimwengu Ousmane Badiane 《The Journal of Agricultural Education and Extension》2013,19(4):399-411
Abstract The paper examines the impact of farmers’ educational attainment on agricultural productivity. More specifically, it evaluates how farmers with vocational training perform compared to those with traditional educational training. A stochastic production frontier and inefficiency effects model is estimated using nationally representative household survey data to analyze the relationship between farmers’ educational attainment and agricultural productivity in Vietnam, while controlling for factors such as gender and farmers’ health status. The results indicate higher returns to vocational training in terms of its impact on raising agricultural productivity, as compared to primary and secondary education. Our findings confirm that significant productivity and welfare gains can be achieved through the promotion of education schemes tailored to the specific technical needs of smallholder or poor farmers. The lack of impact from primary and secondary education signals the need to adjust the curricula of nontraditional educational programmes in rural areas to respond to the technical and other skill needs of farmers. In other words, one general curriculum for everyone may not reap the highest returns to primary and secondary education investment in the context of countries with large farming populations. The originality of the paper resides also in the use of disaggregated education data in terms of formal and non-formal education. In addition, unlike previous studies, the production frontier function and the inefficiency segment are jointly estimated using a one step maximum likelihood estimation (MLE) procedure which guarantees both consistency and efficiency for estimated parameters. 相似文献
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