Sik-Yum Lee
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Explore the profile of Sik-Yum Lee including associated specialties, affiliations and a list of published articles.
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Articles
25
Citations
162
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0
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Recent Articles
1.
Song X, Lee S
Multivariate Behav Res
. 2016 Jan;
37(4):453-77.
PMID: 26816323
This article provides a Bayesian analysis of the multivariate linear model with polytomous variables. The computational burden due to the intractable multiple integrals induced by the polytomous variables and the...
2.
Lee S, Lu B
Multivariate Behav Res
. 2016 Jan;
38(3):375-400.
PMID: 26771224
In this article, a case-deletion procedure is proposed to detect influential observations in a nonlinear structural equation model. The key idea is to develop the diagnostic measures based on the...
3.
Song X, Lee S
Multivariate Behav Res
. 2016 Jan;
38(1):57-79.
PMID: 26771124
This article develops a full maximum likelihood method for obtaining joint estimates of variances and correlations among continuous and polytomous variables with incomplete data which are missing at random with...
4.
Song X, Lee S
Multivariate Behav Res
. 2016 Jan;
40(2):151-77.
PMID: 26760105
In this article, a maximum likelihood approach is developed to analyze structural equation models with dichotomous variables that are common in behavioral, psychological and social research. To assess nonlinear causal...
5.
Lee S, Song X, Poon W
Multivariate Behav Res
. 2016 Jan;
39(1):37-67.
PMID: 26759934
Various approaches using the maximum likelihood (ML) option of the LISREL program and products of indicators have been proposed to analyze structural equation models with non-linear latent effects on the...
6.
Song X, Lee S
Multivariate Behav Res
. 2016 Jan;
41(3):337-65.
PMID: 26750339
In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the...
7.
Lee S, Song X
Multivariate Behav Res
. 2016 Jan;
39(4):653-86.
PMID: 26745462
The main objective of this article is to investigate the empirical performances of the Bayesian approach in analyzing structural equation models with small sample sizes. The traditional maximum likelihood (ML)...
8.
Song X, Lee S, Hser Y
Struct Equ Modeling
. 2009 Dec;
16(2):245-266.
PMID: 20016757
In longitudinal studies, investigators often measure multiple variables at multiple time points and are interested in investigating individual differences in patterns of change on those variables. Furthermore, in behavioral, social,...
9.
Song X, Xia Y, Lee S
Stat Med
. 2009 May;
28(17):2253-76.
PMID: 19472309
Recently, structural equation models (SEMs) have been applied for analyzing interrelationships among observed and latent variables in biological and medical research. Latent variables in these models are typically assumed to...
10.
Xia Y, Song X, Lee S
Br J Math Stat Psychol
. 2008 Dec;
62(Pt 3):529-68.
PMID: 19040790
Structural equation modelling has been widely applied in behavioural, educational, medical, social, and psychological research. The classical maximum likelihood estimate is vulnerable to outliers and non-normal data. In this paper,...