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Xiao Liu; Zhiyong Zhang; Kristin Valentino; Lijuan Wang – Grantee Submission, 2024
Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…
Descriptors: Mediation Theory, Bayesian Statistics, Growth Models, Monte Carlo Methods
Xiao Liu; Zhiyong Zhang; Kristin Valentino; Lijuan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…
Descriptors: Mediation Theory, Bayesian Statistics, Growth Models, Monte Carlo Methods
Enna Wang; Junjie Zhang; Xian Peng; Hongyan Li; Chenguang Teng; Biao Zeng – British Journal of Guidance & Counselling, 2024
This study introduced Satir Growth Model (SGM) into career intervention to enhance Chinese college freshmen's career adaptability. The effect of SGM-based career intervention was examined by the randomised controlled trial design. Results indicated that the experimental group experienced a significant increase in career exploration and career…
Descriptors: Foreign Countries, College Freshmen, Vocational Adjustment, Career Exploration