• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.605-612
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• 2012

Multivariate data are often generated with multiple outcomes in various fields. Multiple outcomes could be mixed as continuous and discrete. Because of their complexity, the data are often dealt with by separately applying regression analysis to each outcome even though they are associated the each other. This univariate approach results in the low efficiency of estimates for parameters. We study the efficiency gains of the multivariate approaches relative to the univariate approach with the mixed data that include continuous and binary outcomes. All approaches yield consistent estimates for parameters with complete data. By jointly estimating parameters using multivariate methods, it is generally possible to obtain more accurate estimates for parameters than by a univariate approach. The association between continuous and binary outcomes creates a gap in efficiency between multivariate and univariate approaches. We provide a guidance to analyze the mixed data.

• The Journal of Information Systems
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• v.32 no.3
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• pp.19-39
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• 2023

Purpose This study aims to identify user experience factors that can enhance both metaverse utilization and satisfaction based on the honeycomb model. For this we presented two research questions: first, what are the experience factors of metaverse users? Second, do metaverse user experience factors impact satisfaction? Design/methodology/approach To address these questions, a mixed-methodology approach is employed, including text mining techniques to analyze online reviews and quantitative econometric analysis to reveal the relationship between user experience factors and satisfaction. A total of 69,880 reviews and ratings data were collected. Findings The analysis revealed eight metaverse user experience factors: entertainment, operability, virtual reality, immersion, economic activity, visual performance, avatar, and sociality, all of which were found to have a positive impact on user satisfaction.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.175-188
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• 2015

This study is about estimation methods for the population pharmacokinetic and pharmacodymic model. This is a nonlinear mixed effect model, and it is difficult to find estimates of parameters because of nonlinearity. In this study, we examined theoretical background of various estimation methods provided by NONMEM, which is the most widely used software in the pharmacometrics area. We focused on estimation methods using a stochastic sampling approach - IMP, IMPMAP, SAEM and BAYES. The SAEM method showed the best performance among methods, and IMPMAP and BAYES methods showed slightly less performance than SAEM. The major obstacle to a stochastic sampling approach is the running time to find solution. We propose new approach to find more precise initial values using an ITS method to shorten the running time.

• Journal of Mechanical Science and Technology
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• v.19 no.11
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• pp.2016-2024
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• 2005

In this work, a mixed beam approach that combines both the stiffness and the flexibility methods has been performed to analyze the coupled composite blades with closed, two-cell cross-sections. The Reissner's semi-complementary energy functional is used to derive the beam force-displacement relations. Only the membrane part of the shell wall is taken into account to make the analysis simple and also to deliver a clear picture of the mixed method. All the cross section stiffness coefficients as well as the distribution of shear across the section are evaluated in a closed-form through the beam formulation. The theory is validated against experimental test data, detailed finite element analysis results, and other analytical results for coupled composite blades with a two-cell airfoil section. Despite the simple kinematic model adopted in the theory, an accuracy comparable to that of two-dimensional finite element analysis has been obtained for cases considered in this study.

• Education of Primary School Mathematics
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• v.20 no.2
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• pp.177-192
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• 2017

In theory, mixed methods that incorporate both quantitative and qualitative approaches can maximize strengths of each method while minimize the short comings of each. Mixed methods research is a feature of educational research nowadays, and the number of studies applied mixed methods research has been gradually increasing. This study investigates how mixed methods research was applied in the field of mathematic education, especially focusing on how qualitative and quantitative methods are combined to best address their research questions. With this in mind, this study carefully selects and analyzes 4 research articles that used mixed methods and were published by Journal of Elementary Mathematics Education in Korea in 2015. This study provides detailed result of qualitative analysis on mixed methods research while other a few previous analysis on mixed methods research were tend to focusing on quantitative analysis, producing numeric quantitative information. The result of this study provides practical and in-depth analysis on how to improve validity and possibility of mixed methods research, addressing alternative ways to combine two different research methods and key elements to take into account.

• IE interfaces
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• v.15 no.2
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• pp.189-198
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• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.969-976
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• 2008

Mixed linear models have been widely used in various correlated data including multivariate survival data. In this paper we extend hierarchical-likelihood(h-likelihood) approach for mixed linear models with right censored data to that for left censored data. We also allow a general random-effect structure and propose the estimation procedure. The proposed method is illustrated using a numerical data set and is also compared with marginal likelihood method.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.141-146
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• 2002

In this article we consider the problem of constructing confidence intervals for a linear regression model with nested error structure. A popular approach is the likelihood-based method employed by PROC MIXED of SAS. In this paper, we examine the ability of MIXED to produce confidence intervals that maintain the stated confidence coefficient. Our results suggest the intervals for the regression coefficients work well, but the intervals for the variance component associated with the primary level cannot be recommended. Accordingly, we propose alternative methods for constructing confidence intervals on the primary level variance component. Computer simulation is used to compare the proposed methods. A numerical example and SAS code are provided to demonstrate the methods.

• Journal of Information Technology Services
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• v.21 no.4
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• pp.105-122
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• 2022

NFTs, which guarantee ownership of digital files using blockchain technology, are the new field for the content industry. The NFT provided new opportunities for content creators to trade digital contents without going through mediation freely. Additionally, collectors and investors can safely and easily own their works without the threat of illegal copies. However, since only a limited number of content creators are participating in the NFT market, there needs to be an influx of various content creators and a process of popularization for this market to grow and develop into the main stage. Furthermore, research on NFT has been limited, and understanding the drivers of creators choosing to participate in NFT is insufficient. Thus, this study aims to identify the factors affecting content creators participating in NFT by applying a mixed-methods approach and presenting practical implications. Using topic modeling and in-depth interviews, this study derives the positive and negative factors and suggests strategies to activate content creators' participation in the NFT market. Through this, we can guide that management implication to reduce the risks and costs of participating in NFTs is needed to encourage the participation of creators. It will also provide insight into ways to develop the NFT content market.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.349-363
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• 2020

Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.