The Korean Journal of Human Development

Article

An Analysis of Longitudinal Data in Human Development Study: With a Special Focus on Latent Growth Model

Author
신택수
Information
pp. 1~28 / 2014 Vol.21 No.3
e-ISSN2982-6845
p-ISSN1226-4474
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Abstract

This study explained characteristics of longitudinal data and analytic tools. It also described how variousmodeling techniques can be applied to longitudinal study. Among the several longitudinal data methods,the study focused on latent growth modeling (LGM) based analytic approaches. LGM is modeled as afunction of an underlying growth process. It also explores effects of specific factors on individual variationin the growth characteristics. In the unconditional analysis, the growth trajectory of mathematicsachievement was followed by nonlinear shape (i.e., concave shape). For the analysis of the conditionalmodel, gender differences were found in terms of both initial status and growth. Although female studentsreported lower initial scores, the growth rate was significantly faster in females than in males. Additionally,low SES students repeatedly reported lower scores across years. In the school level, although significantdifferences were found on the initial status, the initial status and the growth were not significantly related,suggesting school gap sustained. Lastly, reading ability would have a positive influence on mathematicachievement and the proper number of latent classes was deemed to be 4. Other pertaining issues werealso discussed.

Keywords

종단연구 잠재성장모형 다변량분석 다층분석 잠재계층분석 longitudinal study latent growth modeling multivariate analysis multilevel analysis latent class analysis

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