• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.1003-1011
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• 2008

Mixed-effect Poisson regression models are widely used for analysis of correlated count data such as those found in longitudinal studies. In this paper, we consider kernel extensions with semiparametric fixed effects and parametric random effects. The estimation is through the penalized likelihood method based on kernel trick and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of hyperparameters, cross-validation techniques are employed. Examples illustrating usage and features of the proposed method are provided.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.481-492
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• 2017

This paper investigates a convergence rate of a test statistics given by two scale sampling method based on $A\ddot{i}t$-Sahalia and Jacod (Annals of Statistics, 37, 184-222, 2009). This statistics tests for longitudinal data having the existence of long memory dependence driven by fractional Brownian motion with Hurst parameter $H{\in}(1/2,\;1)$. We obtain an upper bound in the Kolmogorov distance for normal approximation of this test statistic. As a main tool for our works, the recent results in Nourdin and Peccati (Probability Theory and Related Fields, 145, 75-118, 2009; Annals of Probability, 37, 2231-2261, 2009) will be used. These results are obtained by employing techniques based on the combination between Malliavin calculus and Stein's method for normal approximation.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.15-35
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• 2020

In research on behavioral studies, significant attention has been paid to the stage-sequential process for multiple latent class variables. We now explore the stage-sequential process of multiple latent class variables using the multivariate latent class profile analysis (MLCPA). A latent profile variable, representing the stage-sequential process in MLCPA, is formed by a set of repeatedly measured categorical response variables. This paper proposes the extended MLCPA in order to explain an association between the latent profile variable and the latent group variable as a form of a two-dimensional contingency table. We applied the extended MLCPA to the National Longitudinal Survey on Youth 1997 (NLSY97) data to investigate the association between of developmental progression of depression and substance use behaviors among adolescents who experienced Authoritarian parental styles in their youth.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.295-304
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• 2015

This paper considers the problem of estimation of the Hurst parameter H ${\in}$ (1/2, 1) from longitudinal data with the error term of a fractional Brownian motion with Hurst parameter H that gives the amount of the long memory of its increment. We provide a new estimator of Hurst parameter H using a two scale sampling method based on $A{\ddot{i}}t$-Sahalia and Jacod (2009). Asymptotic behaviors (consistent and central limit theorem) of the proposed estimator will be investigated. For the proof of a central limit theorem, we use recent results on necessary and sufficient conditions for multi-dimensional vectors of multiple stochastic integrals to converges in distribution to multivariate normal distribution studied by Nourdin et al. (2010), Nualart and Ortiz-Latorre (2008), and Peccati and Tudor (2005).

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.1102-1107
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• 2004

High-speed railway bridges subject to effect of statical loads by temperature change as well as dynamic loads by interaction between vehicle load which run specially fast and behavior of bridges, If suitable longitudinal expansion by temperature change of bridge does not happened, it can cause unhealthy condition for the parts of bridges as well as can generate addition stress to bridges, For these reason, Analysis and Estimation of data about behavior of bridges occupies important factor in that estimate the remaining life of bridges and select the maintenance, repair and retrofit. In this paper, Analysis for the long-term behavior of bridges using Longitudinal displacement and Temperature data that is actuality measured data to the bridges of Seoul-Busan high speed railroad test section has been made.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.301-311
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• 2020

Schwarz's Bayesian information criterion (BIC) is one of the most popular criteria for model selection, that was derived under the assumption of independent and identical distribution. For correlated data in longitudinal studies, Jones (Statistics in Medicine, 30, 3050-3056, 2011) modified the BIC to select the best linear mixed effects model based on the effective sample size where the number of parameters in covariance structure was not considered. In this paper, we propose an extended Jones' modified BIC by considering covariance parameters. We conducted simulation studies under a variety of parameter configurations for linear mixed effects models. Our simulation study indicates that our proposed BIC performs better in model selection than Schwarz's BIC and Jones' modified BIC do in most scenarios. We also illustrate an example of smoking data using a longitudinal cohort of cancer patients.

• The Journal of Korean Association of Computer Education
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• v.23 no.1
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• pp.53-61
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• 2020

In the information society, the ability of learners to use computers to conduct self-directed learning is important. Indeed, the higher the computer's ability to use computers, the more the academic achievement needs to be analyzed. The purpose of this study was to identify longitudinal trajectories of student awareness of ICT literacy and frequency of computer use. We also examined the effects of the longitudinal patterns on academic achievement and college major choice. A non-parametric approach, K-means for longitudinal data(KML) algorithm, was conducted using 9-year longitudinal data from Seoul Education Longitudinal Study (2010-2018). Findings indicated that a pattern presenting a higher awareness of ICT literacy and frequency of computer use showed better academic achievements and was likely to prefer to choose engineering-related majors.

• Proceedings of the Korea Concrete Institute Conference
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• 2001.11a
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• pp.477-482
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• 2001

This paper is to study the effect of longitudinal reinforcement ratios and axial deformation on the frame analysis in reinforced concrete(RC) columns and to investigate the effect of confined concrete core, the length-width ratio and longitudinal steel ratios on frame analysis in Concrete-Filled steel Tubular(CFT) columns. An equation if derived to evaluate the modulus of elasticity for core concrete. The 34 reference data have been collected for the purpose and are processed by the mean of a multiple regression analysis technique. The equation and longitudinal reinforcement ratios was applied to RC columns for structural analysis. Then, the difference of beam moment was identified. In general, the results of analysis was indicated reasonable differences in beam moment, in case of longitudinal reinforcement ratios applied to RC columns when compared with the plain concrete columns. In CFT columns the equation was also applied in order to the effect of confined concrete core on structural analysis. Beam moment was increased as volumetric ratio of lateral steel was decreased. The effect of longitudinal steel ratios was investigated in CFT columns and was confirmed beam moment variety. The result was appeared reasonable difference in beam moment as longitudinal steel was increased.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.9
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• pp.2770-2781
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• 1996

Longitudinal shear modulus of continuous fiber reinforced 2-phase composites is predicted by theoretical and numerical analysis methods. In this paper, circular, hexagonal and rectangular shapes of reinforced fiber are considered using unit cell concept. And fiber array is regular rectangular and hexagonal fiber arrangement. Longitudinal shear modulus is a function of fiber distribution pattern and fiber volume change. It is found that the rectangular array has a higher longitudinal shear modulus than the hexagonal one. Also, the rectangular fiber shape in lower fiber volume fraction and the circular fiber shape in higher fiber volume fraction show the higher longitudinal shear modulus. And it has been found that the theoretical and numerical predictions of the longitudinal shear modulus give a good agreement with the experimental data at lower fiber volume fraction. Both the distance and stress transfer between the fibers are discussed as the major determing factors.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.281-296
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• 2020

Repeated outcomes from the same subjects are referred to as longitudinal data. Analysis of the data requires different methods unlike cross-sectional data analysis. It is important to model the covariance matrix because the correlation between the repeated outcomes must be considered when estimating the effects of covariates on the mean response. However, the modeling of the covariance matrix is tricky because there are many parameters to be estimated, and the estimated covariance matrix should be positive definite. In this paper, we consider analysis of multivariate longitudinal data via two modeling methodologies for the covariance matrix for multivariate longitudinal data. Both methods describe serial correlations of multivariate longitudinal outcomes using a modified Cholesky decomposition. However, the two methods consider different decompositions to explain the correlation between simultaneous responses. The first method uses enhanced linear covariance models so that the covariance matrix satisfies a positive definiteness condition; in addition, and principal component analysis and maximization-minimization algorithm (MM algorithm) were used to estimate model parameters. The second method considers variance-correlation decomposition and hypersphere decomposition to model covariance matrix. Simulations are used to compare the performance of the two methodologies.