The Optimal Starting Model to Search for the Accurate Growth Trajectory in Latent Growth Models

Frontiers in Psychology

Minjung Kim¹ 

关键词: latent growth models;    latent curve models;    growth analysis;    model selection;    specification search;    starting model;    model building;    growth curve;   

DOI  :  10.3389/fpsyg.2018.00349

学科分类：心理学（综合）

来源: Frontiers

【 摘 要 】

This simulation study aims to propose an optimal starting model to search for the accurate growth trajectory in Latent Growth Models (LGM). We examine the performance of four different starting models in terms of the complexity of the mean and within-subject variance-covariance (V-CV) structures when there are time-invariant covariates embedded in the population models. Results showed that the model search starting with the fully saturated model (i.e., the most complex mean and within-subject V-CV model) recovers best for the true growth trajectory in simulations. Specifically, the fully saturated starting model with using ΔBIC and ΔAIC performed best (over 95%) and recommended for researchers. An illustration of the proposed method is given using the empirical secondary dataset. Implications of the findings and limitations are discussed.

【 授权许可】

CC BY