关键词: 追踪研究, 潜变量混合增长模型, 潜变量增长曲线模型, 多层线性模型

Abstract: Developmental research involves the identification of individual differences in change as well as understanding the process of change itself. The contemporary approach to the analysis of change, as Hierarchical Linear Model (HLM) and Latent Growth Curve Model (LGCM), has focused on growth curve modeling that explicitly considers both intraindividual change and interindividual differences in such change, but treats the data as if collected from a single population. This assumption of homogeneity in the growth parameters is often unrealistic. If heterogeneity is ignored, statistical analyses and their effects can be seriously biased. This paper presents a procedure that accounts for sample heterogeneity---Latent Growth Mixed Model (LGMM)---and their application to longitudinal data. In addition, the difference of HLM and LGMM, and the difference of LGCM and LGMM were discussed briefly

Key words: longitudinal study, latent growth mixed model, hierarchical linear model, latent growth curve model