• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.957-981
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• 2017

A generalized linear mixed model is an extension of a generalized linear model that allows random effect as well as provides flexibility in developing a suitable model when observations are correlated or when there are other underlying phenomena that contribute to resulting variability. We describe maximum likelihood estimation methods for logistic regression models that include random effects - the Laplace approximation, Gauss-Hermite quadrature, adaptive Gauss-Hermite quadrature, and pseudo-likelihood. Applications are provided with social science problems by analyzing the effect of mental health and life satisfaction on volunteer activities from Korean welfare panel data; in addition, we observe that the inclusion of random effects in the model leads to improved analyses with more reasonable inferences.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.289-294
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• 2015

Linear mixed models are commonly used in the clinical pharmaceutical studies to analyze repeated measures such as the crossover study data of bioequivalence studies. In these models, random effects describe the correlation between repeated outcomes and variance-covariance matrix explain within-subject variabilities. Bioequivalence analysis verifies whether a 90% confidence interval for geometric mean ratio of Cmax and AUC between reference drug and test drug is included in the bioequivalence margin [0.8, 1.25] performed using linear mixed models with period, sequence and treatment effects as fixed and sequence nested subject effects as random. A Levofloxacin study is referred to for an example of real data analysis.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.405-414
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• 2002

We consider the problem of estimating the error variance of in a two-way mixed-effects ANOVA model using noninformative priors. First, we derive Jeffreys' prior, a reference prior, and matching priors. We then provide marginal posterior distributions under those noninformative priors. Finally, we provide graphs of marginal posterior densities of the error variance and credible intervals for the error variance in two real data set and compare these credible intervals.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.923-932
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• 2014

The Hurdle model can to analyze zero-inflated count data. This model is a mixed model of the logit model for a binary component and a truncated Poisson model of a truncated count component. We propose a new hurdle model with a general heterogeneous random effects covariance matrix to analyze longitudinal zero-inflated count data using modified Cholesky decomposition. This decomposition factors the random effects covariance matrix into generalized autoregressive parameters and innovation variance. The parameters are modeled using (generalized) linear models and estimated with a Bayesian method. We use these methods to carefully analyze a real dataset.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.361-369
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• 2015

A general linear mixed-effects model is often used to analyze repeated measurement experiment data of a continuous response variable. However, a general linear mixed-effects model can give improper analysis results when simultaneously detecting heteroscedasticity and the non-normality of population distribution. To achieve a more robust estimation, we used a heavy-tailed linear mixed-effects model for a more exact and reliable analysis conclusion than a general linear mixed-effects model. We also provide reliability analysis results for further research.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.129-137
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• 2002

This paper suggests a generalized logit model with mixed effects for analysing frequency data in multi-contingency table. In this model nominal response variable is assumed to be polychotomous. When some factors are fixed but considered as ordinal and others are random, this paper shows how to use baseline-category logits to incoporate the mixed-effects of those factors into the model. A numerical algorithm was used to estimate model parameters by using marginal log-likelihood.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.511-520
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• 2010

The Pharmacokinetic model is a complex nonlinear model with pharmacokinetic parameters that is some-times represented by a complex form of differential equations. A population pharmacokinetic model adds individual variability using the random effects to the pharmacokinetic model. It amounts to the nonlinear mixed effect model. This paper, reviews the population pharmacokinetic model from a statistical viewpoint; in addition, a population pharmacokinetic model is also applied to the real clinical data along with a review of the statistical meaning of this model.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.353-366
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• 2018

This study uses mixed-effects models to predict thigh soft tissue artefact (STA), relative movement of soft tissue such as skin to femur occurring during hip joint motions. The random effects in the model were defined as STA and the fixed effects in the model were considered as skeletal motion. Five male subjects without musculoskeletal disease were selected to perform various hip joint rotational motions. Linear mixed-effects models were applied to markers' position vectors acquired from non-invasive method, photogrammetry. Predicted random effects showed similar patterns of STA among subjects. Large magnitudes of STA appeared on the points near the hip joint regardless of sides; however, small values appeared on the distal anterior.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.247-253
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• 2006

본고는 주요 댐호수의 휴양가치를 댐호수의 특성별로 도출하고자 실제로 댐호수를 선택한 행위를 분석하고, 아울러 선택실험을 통해 가상적으로 설정된 특성을 가진 댐을 방문할지를 선택하도록 하여 그 결과를 분석하기도 하였다. 또한 현시선호된 선택과 진술선호선택을 모두 결합하여 분석하는 기법도 사용하였다. 분석결과 진술선호자료와 현시선호자료간의 이질성이 상당한 것으로 나타났으나 두 자료를 결합함으로써 모든 특성변수들이 만족도에 미치는 영향이 직관과 부합되도록 도출되었다. 댐호수의 수량과 수질 모두가 레크리에이션 가치에 영향을 미치는 것으로 나타났으나, 특히 수질개선의 편익 증가효과가 매우 크다는 것이 확인되었다. 그 외에도 홍보관, 주변 숙박시설 및 음식점, 인근 휴양지와의 연계성 등도 휴양가치 증가에 영향을 미치는 주요 변수로 파악되었다.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.513-524
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• 2016

The purpose of this study was to open two classes with the name of $21^{st}$ Leadership, run with two different hybrid teaching styles which are hybrid LZ type and hybrid lz type, and compare them with each other in order to analyze their effectiveness of hybrid model of the subject. The subjects of this study were 64 students who took these classes, and statistical analysis were analyzed through SPSS 21.0 program. As a result of the analysis, first, there were significant development in terms of the knowledge of leadership in both LZ and lz model. but the result of final exam in the group lz was shown only significant development. Second, in the case of unconditional self-acceptance there was significant development only in the group lz. Third, the development of leadership skills was shown only in the group lz. Implications of these results were concluded that the lz is more suitable for the subject of $21^{st}$ Leadership because this model can provide much more opportunities to develope interpersonal relationship skill than LZ model. In addition, suggestions for future research were discussed.