S
Sungjin Hong
Researcher at University of Illinois at Urbana–Champaign
Publications - 15
Citations - 954
Sungjin Hong is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Population & Socioeconomic status. The author has an hindex of 11, co-authored 15 publications receiving 886 citations. Previous affiliations of Sungjin Hong include Hamilton Health Sciences & University of Western Ontario.
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Journal ArticleDOI
The influence of economic development level, household wealth and maternal education on child health in the developing world
Michael H. Boyle,Yvonne Racine,Katholiki Georgiades,Dana Snelling,Sungjin Hong,Walter Omariba,Patricia Hurley,Purnima Rao-Melacini +7 more
TL;DR: There are inextricable links among different strategies for improving child health and that policy planners, associating benefits with these strategies, must take into account the strong moderating impact of national context.
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A Comparative Study on Parameter Recovery of Three Approaches to Structural Equation Modeling
TL;DR: In this paper, the authors conduct a simulation study to evaluate the relative performance of these three approaches in terms of parameter recovery under different experimental conditions of sample size, data distribution, and model specification.
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Chronic physical health conditions and disability among Canadian school-aged children: a national profile.
Janette McDougall,Gillian King,David J. De Wit,Linda T. Miller,Sungjin Hong,David R. Offord,John LaPorta,Katherine Meyer +7 more
TL;DR: A national health and disability profile of Canadian school-aged children based on the World Health Organization's definitions of health condition and disability that would facilitate international comparisons of child health data is provided.
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The Differential Impact of Early Father and Mother Involvement on Later Student Achievement
TL;DR: Findings provide partial support for the hypothesized differential relationship between fathers' and mothers' early parenting and later student achievement.
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Shifted factor analysis—Part I: Models and properties
TL;DR: Shifted factor models as discussed by the authors have been proposed to deal with the problem of factor shifts in sequential data, where the profiles of the latent factors shift position up or down the sequence of measurements: such shifts disturb multilinearity and so standard factor/component models no longer apply.