comparison of three growth modeling techniques in the multilevel analysis of longitudinal academic achievement scores: Latent growth modeling, hierarchical linear modeling, and longitudinal profile analysis via multidimensional scaling |
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| Authors: | Tacksoo Shin |
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| Institution: | (1) Department of Education, Seoul National University, San 56-1, Sillim-dong, 151-742 Gwanak-gu, Seoul, Korea |
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| Abstract: | This study introduces three growth modeling techniques: latent growth modeling (LGM), hierarchical linear modeling (HLM),
and longitudinal profile analysis via multidimensional scaling (LPAMS). It compares the multilevel growth parameter estimates
and potential predictor effects obtained using LGM, HLM, and LPAMS. The purpose of this multilevel growth analysis is to alert
applied researchers to selected analytical issues that are required for consideration in decisions to apply one of these three
approaches to longitudinal academic achievement studies. The results indicated that there were no significant distinctions
on either mean growth parameter estimates or on the effects of potential predictors to growth factors at both the student
and school levels. However, the study also produced equivocal findings on the statistical testing of variance and covariance
growth parameter estimates. Other practical issues pertaining to the three growth modeling methods are also discussed. |
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| Keywords: | longitudinal academic achievement study multilevel growth analysis latent growth modeling hierarchical linear modeling longitudinal profile analysis via multidimensional scaling |
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