• Communications for Statistical Applications and Methods
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• v.29 no.3
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• pp.353-371
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• 2022

This paper analyzes death counts after World War II of several countries to identify and to compare their stochastic structures. The stochastic structures that this paper entertains are three structural time series models, a local level with a random walk model, a fixed local linear trend model and a local linear trend model. The structural time series models assume that a time series can be formulated directly with the unobserved components such as trend, slope, seasonal, cycle and daily effect. Random effect of each unobserved component is characterized by its own stochastic structure and a distribution of its irregular component. The structural time series models use the Kalman filter to estimate unknown parameters of a stochastic model, to predict future data, and to do filtering data. This paper identifies the best-fitted stochastic model for three types of death counts (Female, Male and Total) of each country. Two diagnostic procedures are used to check the validity of fitted models. Three criteria, AIC, BIC and SSPE are used to select the best-fitted valid stochastic model for each type of death counts of each country.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.605-629
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• 2023

This paper proposes some diagnostics procedures for the skew-t linear regression model with censored response. The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and student's-t distributions as special cases. Inspired by the power and wide applicability of the EM-type algorithm, local and global influence analysis, based on the conditional expectation of the complete-data log-likelihood function are developed, following Zhu and Lee's approach. For the local influence analysis, four specific perturbation schemes are discussed. Two real data sets, from education and economics, which are right and left censoring, respectively, are analyzed in order to illustrate the usefulness of the proposed methodology.

• Journal of Periodontal and Implant Science
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• v.52 no.1
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• pp.54-64
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• 2022

Purpose: This in vitro study was conducted to evaluate the effects of different debridement techniques and conditioning procedures on root surface morphology and blood clot stabilization. Methods: Two debridement techniques (curette [CU] vs. high-speed ultrasound [US]) and 2 conditioning procedures (ethylenediaminetetraacetic acid [EDTA] and phosphoric acid [PA]) were used for the study. Seven experimental groups were tested on root surfaces: 1) no treatment (C); 2) CU; 3) US; 4) CU+EDTA; 5) US+EDTA; 6) CU+PA; and 7) US+PA. Three specimens per group were observed under scanning electron microscopy (SEM) for surface characterization. Additional root slices received a blood drop, and clot formation was graded according to the blood element adhesion index by a single operator. Data were statistically analyzed, using a threshold of P<0.05 for statistical significance. Results: The C group displayed the most irregular surface among the tested groups with the complete absence of blood traces. The highest frequency of blood component adhesion was shown in the CU+EDTA group (P<0.05), while no differences were detected between the CU, US+EDTA, and CU+PA groups (P<0.05), which performed better than the US and US+PA groups (P<0.05). Conclusions: In this SEM analysis, EDTA and conventional manual scaling were the most efficient procedures for enhancing smear layer removal, collagen fiber exposure, and clot stabilization on the root surface. This technique is imperative in periodontal healing and regenerative procedures.

• Journal of Korea Trade
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• v.27 no.3
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• pp.179-198
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• 2023

Purpose - There is a paucity of literature dealing with exporters' compliance issues in e-commerce exports. This study aims to fill this gap in the literature by exploring customs initiatives to facilitate the e-commerce exports of small and medium-sized enterprises (SMEs) in the changed compliance environment. The central question of this study was divided into five subquestions: first regarding the pros and cons of trade facilitation measures for Korean e-commerce export clearance; second and third questions about risk and compliance management for facilitation fourth about instruments, the changes in Korean SME compliance burden in e-commerce exports, and ways to improve trade facilitation for e-commerce exports. Design/methodology - This study adopts a qualitative approach using a case study method to understand the SME experience in Korean e-commerce export compliance procedures. A qualitative method was selected to answer research questions requiring an in-depth understanding of the regulatory procedures of customs administration and exporters' compliance burden. Because this study addresses the changing compliance environment for which statistical data is insufficient, a quantitative method is considered inappropriate. Based on the approach, data were collected using multiple sources, including an extensive literature review, interviews, and field observations. Thematic pattern matching was applied to interpret the data. Findings - This study examined ways to support SMEs in the changed e-commerce export compliance environment. Facilitation measures for e-commerce exports have contributed to SME access to global markets, simplifying export clearance procedures, and saving exporters' compliance costs. However, such instruments are limited in promoting SME compliance capabilities to cope with intensified competition and strengthened controls over foreign exporters in cross-border e-commerce. Therefore, this study highlights the importance of reshaping facilitation measures for e-commerce exports based on risk and compliance management theories to a system encouraging exporters' voluntary compliance. Originality/value - This study's academic significance derives from verifying the relationship between trade facilitation instruments and risk and compliance management procedures using an actual case in Korea. It is also of practical importance in navigating the directions for improving facilitation measures for e-commerce exports in a changed compliance environment.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.95-111
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• 2010

Recently, there have been lots of study for disease-genetic association using SNPs and haplotypes. Statistical methods and tools for various types of data are developed by many researchers. However, there is no unified software which can handle most of major analysis, and the methods and manners to deal with data are quite different through softwares. And thus it is not easy to researcher to choose proper software. In this study, we devide analyzing procedures into three steps: preliminary analysis, population-based analysis and family-based analysis. We review the statistical methods for each step and compare the features of the FBAT, SAS/Genetics, SAGE and R as major integrating softwares for genetic study.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.713-723
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• 2019

Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.357-364
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• 1997

The early detection of breast cancer is clearly a key ingredient for reducing breast cancer mortality. Microcalcification is the only visible feature of the DCIS's(ductal carcinoma in situ) which consist 15 ~ 20% of screening-detected breast cancer. Therefore, the analysis of the shapes and distributions of microcalcifications is very significant for the early detection. The automatic detection procedures have b(:on the concern of digital image processing for many years. We proposed here one efficient method which is essentially statistical pattern classification accelerated by one representative feature, correlation coefficient. We compared the results by this additional feature with results by a simple gray level thresholding. The average detection rate was increased from 48% by gray level feature only to 83% by the proposed method The performances were evaluated with TP rates and FP counts, and also with Bayes errors.

• Progress in Medical Physics
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• v.26 no.2
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• pp.59-71
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• 2015

The goal of quality assurance (QA) is to minimize systematic errors in order to maintain the quality of a certain process. Statistical process control (SPC) has been utilized for QA in radiation therapy field since 2005 and is changing QA paradigm. Its purpose is to maintain a process within the given control limits while monitoring of error trends such as variation or dispersion. SPC can be applied to all QA aspects of radiotherapy; however, a medical physicist should have enough knowledge about the application of SPC to QC/QA procedures. In this paper, the author introduce a concept of SPC and review some previously reported studies those used SPC for QA in radiation therapy.

• YAKHAK HOEJI
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• v.44 no.4
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• pp.308-314
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• 2000

Logarithmic transformation of pharmacokinetic parameters is routinely used in bioequivalence studies based on pharmacokinetic and statistical grounds by the United States Food and Drug Administration (FDA), European Committee for Proprietary Medicinal Products (CPMP), and Japanese National Institute of Health and Science (NIHS). Although it has not yet been recommended by the Korea Food and Drug Administration (KFDA), its use is becoming increasingly necessary in order to harmonize with international standards. In the present study, statistical procedures for the analysis of a bioequivalence based on the log transformation and a related SAS procedure were demonstrated in order to aid the understanding and application. The AUC parameters used in this demonstration were taken from the previous bioequivalence study for two aceclofenac tablets, which were performed in a single-dose crossover design. Analysis of variance (ANOVA), statistical power to detect 20% difference between the tablets, minimum detectable difference and confidence intervals were all assessed following log-transformation of the data. Bioequivalence of two aceclofenac tablets was then estimated based on the guideline of FDA. Considering the international effort for harmaonization of guidelines for bioequivalence tests, this approach may require a further evaluation for a future adaptation in the Korea Guidelines of Bioequivalence Tests (KGBT).

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.65-73
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• 2023

Contemporary biomedical data often involve an ill-posed problem owing to small sample size and large number of multi-collinear variables. Partial least squares (PLS) method could be a plausible alternative to an ill-conditioned ordinary least squares. However, in the case of a PLS model that includes a random-effect, how to deal with a random-effect or mixed effects remains a widely open question worth further investigation. In the present study, we propose a modified multivariate PLS method implementing mixed-effect model (PLSM). The advantage of PLSM is its versatility in handling serial longitudinal data or its ability for taking a randomeffect into account. We conduct simulations to investigate statistical properties of PLSM, and showcase its real clinical application to predict treatment outcome of esthetic surgical procedures of human faces. The proposed PLSM seemed to be particularly beneficial 1) when random-effect is conspicuous; 2) the number of predictors is relatively large compared to the sample size; 3) the multicollinearity is weak or moderate; and/or 4) the random error is considerable.