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http://dx.doi.org/10.7465/jkdi.2017.28.1.1

A longitudinal data analysis for child academic achievement with Korea welfare panel study data  

Lee, Naeun (Department of Statistics, Duksung Women's University)
Huh, Jib (Department of Statistics, Duksung Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.1, 2017 , pp. 1-10 More about this Journal
Abstract
Longitudinal data of Korean child academic achievement have been used to find the significant exploratory variables under the assumption of independent repeated measured data. Using the exploratory variables in previous research works, we analyze the linear mixed model incorporating the fixed and random effects for child academic achievement to detect the significant exploratory variables. Korea welfare panel study data observed three times between 2006 and 2012 by additional survey for children. The child academic achievement is evaluated by the sum of academic achievements of Korean, English and Mathematics. We also investigate the multicollinearity and the missing mechanism and select some popular correlation matrices to analyze the linear mixed model.
Keywords
Correlation matrix; fixed effect; linear mixed model; missing at random; multicollinearity; random effect;
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Times Cited By KSCI : 9  (Citation Analysis)
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