A systematic approach for identifying level-1 error covariance structures in latent growth modeling

Cherng G. Ding*, Ten Der Jane, Chiu Hui Wu, Hang Rung Lin, Chih Kang Shen

*Corresponding author for this work

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which, however, is not systematically addressed in the literature. In this study, we first discuss characteristics of various covariance structures and their nested relations, based on which we then propose a systematic approach to facilitate identifying a plausible covariance structure. A test for stationarity of an error process and the sequential chi-square difference test are conducted in the approach. Preliminary simulation results indicate that the approach performs well when sample size is large enough. The approach is illustrated with empirical data. We recommend that the approach be used in LGM empirical studies to improve the quality of the specification of the error covariance structure.

原文English
頁(從 - 到)444-455
頁數12
期刊International Journal of Behavioral Development
41
發行號3
DOIs
出版狀態Published - 1 五月 2017

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