Song Q Y, Wu Y Z
Department of Health Statistics College of Preventive Medicine, Third Military Medical University, Chongqing 400038, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2017 Aug 10;38(8):1132-1135. doi: 10.3760/cma.j.issn.0254-6450.2017.08.027.
To discuss the latent variable growth curve model of longitudinal data and give its implementation method in Mplus. The application of Mplus software has been used to deal with the longitudinal data of mental health status of college students in an university. Results show that the model can process the longitudinal data with latent variables, which can compare the differences of the overall development trend and individual development, also taking a covariate into the model to improve the effect of model fitting. Using Mplus software to process the longitudinal data with latent variables, the program is simple and easy to operate. This study provides the latent variable growth curve model of longitudinal data and its procedure of implementation in Mplus, and the statistical methodology guidance and reference for practical applications of epidemiological cohort study.
探讨纵向数据的潜变量增长曲线模型，并给出其在Mplus中的实现方法。运用Mplus软件处理某高校大学生心理健康状况的纵向数据。结果表明，该模型能够处理带有潜变量的纵向数据，可比较总体发展趋势和个体发展的差异，还可将协变量纳入模型以提高模型拟合效果。使用Mplus软件处理带有潜变量的纵向数据，程序简单易操作。本研究提供了纵向数据的潜变量增长曲线模型及其在Mplus中的实现过程，为流行病学队列研究的实际应用提供了统计方法学指导和参考。
