• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.529-540
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• 2015

A cross-over design is frequently used in clinical trials (especially in bioequivalence tests with a parametric method) for the comparison of two treatments. Missing values frequently take place in cross-over designs in the second period. Usually, subjects that have missing values are removed and analyzed. However, it can be unsuitable in clinical trials with a small sample size. In this paper, we compare single imputation methods in a $2{\times}2$ cross-over design when missing values exist in the second period. Additionally, parametric and nonparametric methods are compared after applying single imputation methods. A Monte-Carlo simulation study compares type I error and the power of methods.

• Journal of the korean veterinary medical association
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• v.36 no.7
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• pp.602-614
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• 2000

• Journal of the korean veterinary medical association
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• v.36 no.6
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• pp.517-525
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• 2000

실험은 과학적 사실을 규명하기 위한 적극적인 수단이다. 실험이란 문자 그대로 검정 (test)을 의미하는데 좀 더 공식적으로 표현하자면 '연구자가 어떤 체계(system) 혹은 과정 (process)속으로 의도하는 변화를 투입 변수 (input variable)로 넣었을 때 그 결과로 얻게되는 반응에서 어떠한 변화가 초래되었는지 그 원인을 찾아내는 일련의 검정(series of tests)'이라고 정의할 수 있다. 넓은 의미에서 볼 때 실험의 형태는 발생조사(outbreak investigation)와 같이 현장 (fidld)에서 진행되는 관찰연구 (observational study)와 실험실 연구로 대별된다. 어떠한 연구형태이든 실험의 객관성을 달성하기 위해서는 연구의 목적에 합당한 실험계획을 작성하는 것이 필수적이다. 아무리 완벽하게 실험을 수행했다고 하더라도 실험계획에서 심각한 문제가 있다면 그 결과에 대해서는 신뢰성을 부여할 수 없기 때문이다. 본 논문에서는 실험을 계획할 때 적용되는 원리와 분산분석에서의 다중비교 및 의학연구에서 활용빈도가 높은 교차계획법 (crossover design)에 대하여 소개하고자 한다.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.39-52
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• 2007

Crossover trials of new drugs in the treatment of angina pectoris, which frequently use treadmill exercise test for the assessment of its efficacy, produce censored survival times. In this paper we consider analysis approaches for censored survival times from crossover trials. Previously, a stratified Cox model for paired observation and nonparametric methods have been presented as possible analysis methods. On the other hand, the differences of two survival times would produce interval-censored survival times and we propose a Cox model for interval-censored data as n alternative analysis method. Example data is analyzed in order to compare these different methods.

• Journal of the Korean Society for Library and Information Science
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• v.31 no.3
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• pp.165-208
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• 1997

The purpose of this study is to evaluate the characteristics of user interface that affect the searching behavior of OPAC users. and then to propose how to design user-friendly interfaces of OPACS. An experiment was conducted on two systems with different interfaces to grasp the effect of user interface to search process and search outcome. A $2\times2$ cross-over design was used for the experiment. Sixty five searchers participated in the experiment. Several statistical techniques such as carry-over effect and system effect of a $2\times2$ cross-over design, $\chi^2$ test, t- test, McNemar test, test of marginal homogeneity through maximum likelihood method, factor analysis, regression analysis, and analysis of variance were applied according to the hypotheses tested and the data analyzed.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1439-1448
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• 2013

The analysis of variance for randomized block design or two way classification data is well known. In this paper, particularly, we considered two stage nested design in which the levels of one factor is not identical for different levels of another factor. We investigate the structural properties of two stage nested design and the properties of error sum of squares for random effect model. For the application of two way nested design, we consider two-period crossover design which is used commonly for the equivalence test to bio-similar product. The confidence interval estimation of the difference of two population means in the crossover design is discussed based on statistical package SPSS.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.259-267
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• 2018

The subset-sum problem is to find out whether or not the element sum of a subset within a finite set of numbers is equal to a given value. The problem is a well-known NP-complete problem, which is difficult to solve within a polynomial time. Genetic algorithm is a method for finding the optimal solution of a given problem through operations such as selection, crossover, and mutation. Dynamic programming is a method of solving a given problem from one or several subproblems. In this paper, we design and implement a genetic algorithm that solves the subset-sum problem, and experimentally compared the time performance to find the answer with the case of dynamic programming method. We selected a total of 17 test cases considering the difficulty in a set with 63 elements of positive number, and compared the performance of the two algorithms. The presented genetic algorithms showed time performance improved by 84% on 13 of 17 problems when compared with dynamic programming.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.915-922
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• 2013

Quantile regression can estimate multiple conditional quantile functions of the response, and as a result, it provide comprehensive information of the relationship between the response and the predictors. However, when estimating several conditional quantile functions separately, two or more estimated quantile functions may cross or overlap and consequently violate the basic properties of quantiles. In this paper, we propose a new stepwise method to estimate multiple non-crossing quantile functions using constraints on the kernel coefficients. A simulation study are presented to demonstrate satisfactory performance of the proposed method.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.193-206
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• 2002

A signal optimization model is proposed by applying the Cell-Transmission Model(CTM) as an embedded traffic flow model to estimate a system-optimal signal timing plan in a transportation network composed of signalized intersections. Beyond the existing signal-optimization models, the CTM provides appropriate theoretical and practical backgrounds to simulate oversaturation phenomena such as shockwave, queue length, and spillback. The model is formulated on the Mixed-Integer Programming(MIP) theory. The proposed model implies a system-optimal in a sense that traffic demand and signal system cooperate to minimize the traffic network cost: the demand departing from origins through route choice behavior until arriving at destinations and the signal system by calculating optimal signal timings considering the movement of these demand. The potential of model's practical application is demonstrated through a comparison study of two signal control strategies: optimal and fixed signal controls.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.75-88
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• 2001

Signal optimization model for alternative use of lanes at a signalized intersection with an stop-line added backward was presented in this paper. The simulation results shot-ed that the traffic fed from the stop-line passed the intersection in each specified phasing interval for left and through traffic. The experimental results indicated that the proposed model was much superior to traditional signal optimization methodology in reducing delay, fuel consumption, and disutility index for delay and stops. The effects for reducing delay were greater than those for doing fuel consumption and disutility index due to the added stop-line. The proposed model is expected to alleviate traffic congestion at intersections, both which have no left turn pocket, and which have large left turn volume. The model is recommended to adapted for intersections spaced long among them with no near driveway.