Using design-based latent growth curve modeling with cluster-level predictor to address dependency

Jiun-Yu Wu*, Oi Man Kwok, Victor L. Willson

*此作品的通信作者

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15 引文 斯高帕斯(Scopus)

摘要

The authors compared the effects of using the true Multilevel Latent Growth Curve Model (MLGCM) with single-level regular and design-based Latent Growth Curve Models (LGCM) with or without the higher-level predictor on various criterion variables for multilevel longitudinal data. They found that random effect estimates were biased when the higher-level predictor was not included and that standard errors of the regression coefficients from the higher-level were underestimated when a regular LGCM was used. Nevertheless, random effect estimates, regression coefficients, and standard error estimates were consistent with those from the true MLGCM when the design-based LGCM included the higher-level predictor. They discussed implication for the study with empirical data illustration.

原文English
頁(從 - 到)431-454
頁數24
期刊Journal of Experimental Education
82
發行號4
DOIs
出版狀態Published - 2 10月 2014

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