• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.479-496
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• 2003

We investigate logit confidence intervals for the odds ratio based on the delta method. These intervals are constructed using pseudo-Bayes estimators. The Gart method and Agresti method smooth the observed counts toward the model of equiprobability and independence, respectively. We obtain better coverage probability by smoothing the observed counts toward the pseudo-Bayes estimators in 2$\times$2 table. We also improve legit confidence intervals in 2$\times$2$\times$K tables by generalizing these ideas. Utilizing pseudo-Bayes estimators, we obtain better coverage probability by smoothing the observed counts toward the conditional independence model, no three-factor interaction model and saturated model in 2$\times$2$\times$K tables.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.135-144
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• 2003

This work is concerned with comparison of the recently developed disparity measures for the partial association model in three dimensional categorical data. Data are generated by using simulation on each term in the log-linear model equation based on the partial association model, which is a proposed method in this paper. This alternative Monte Carlo methods are explored to study the behavior of disparity measures such as the power divergence statistic I(λ), the Pearson chi-square statistic X$^2$, the likelihood ratio statistic G$^2$, the blended weight chi-square statistic BWCS(λ), the blended weight Hellinger distance statistic BWHD(λ), and the negative exponential disparity statistic NED(λ) for moderate sample sizes. We find that the power divergence statistic I(2/3) and the blended weight Hellinger distance family BWHD(1/9) are the best tests with respect to size and power.

• Journal of Technology Innovation
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• v.13 no.3
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• pp.175-196
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• 2005

This Paper examines analytic studies of the evaluation system used for evaluating government-supported R&D Institutes (GSRIs), and designs a new model for analyzing the evaluation system's effectiveness. The analytic models in existing studies use the meta evaluation and balanced scorecard (BSC) models. However, theses studies focused on the structure and elements of the evaluation system for examples, the appropriateness of the elements within the evaluation system and the balance of the evaluation index. Accordingly, the effectiveness of the GSRI evaluation system, that is, the evaluation's influence on GSRI performance improvement was not analyzed. This study uses the institution theory and contingency theory perspectives as related to government organization management to develop an analytical model of GSRI evaluation system effectiveness. The new model proposes an analytical approach for improving the effectiveness of the GSRI evaluation system in an institutionalized environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.93-102
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• 1995

In this study we are concerned with the diagnostics method of cross-classified categorical data using logistic regression model of binary response models for cell proportions. under this model, we could examine the goodness-of-fit of the models using Pearson's $x^2$test statistic and likelihood ratio statistic. Under this model, these statistics are assumed that sample survey schemes are with replacement sampling model. But these statistics are often inappropriate for analysing contingency tables consists of complex sampling schemes obtained sample survey data. In this study we are examined diagnostics procedures detecting any outlying cell proportions and influential observations on design space in logistic regression modeltake account of the survey design effects.

• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.167-174
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• 2015

Information security organization has normally been organized under the IT department. However, as the importance of information security has gradually increased, the way of information security organized for enterprise security management has become a noteworthy issue. The need for separation of Information security organization from IT department is growing, such as restriction on the concurrent positions in CIO and CISO. Nowadays there are many studies about Information security organization while relatively there has been minimal research regarding a departmentalization. For these reasons this study proposes a Information Security Departmentalization Model which is based on business risk and reliance on the IT for effectively organizing Information security organization, using Contingency theory. In addition, this study classified the position of Information security organization into Planning & Coordination, Internal Control, Management and IT and analyze the strengths and weaknesses of each case.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.184-186
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• 2005

Increasement of power demand rapid industrial growth has led the expansion of power system, and it caused construction of large power transmission line(like 765kV T/L) and substation. If there are T/L faults (route contingency etc), it lead to the large scale black out in SEOUL AREA (the center of load). To minimize damage which caused by the large scale black out, KEPCO selects the method of load shadding. In this work, instead of general method of load shadding, We study the application of UVLS model to decrease the load shadding in SEOUL AREA. The study result of using the UVLS model showed that the amont of load shadding can be decreased about 400 MW compare to the existing load shadding system.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.197-212
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• 2002

When assessing goodness-of-fit of a model, a small subset of deviating observations can give rise to a significant lack of fit. It is therefore important to identify such observations and to assess their effects on various aspects of analysis. A Cook's distance measure is usually used to detect influential observation. But it sometimes is not fully effective in identifying truly influential set of observations because there may exist masking or swamping effects. In this paper we confine our attention to influential subset In GLMs such as logistic regression models and loglinear models. We modify a backwards stepping algorithm, which was originally suggested for detecting outlying cells in contingency tables, to detect influential observations in GLMs. The algorithm consists of two steps, the identification step and the testing step. In identification step we Identify influential observations based on influencial measures such as Cook's distances. On the other hand in testing step we test the subset of identified observations to be significant or not Finally we explain the proposed method through two types of dataset related to logistic regression model and loglinear model, respectively.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.587-593
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• 2012

We study Bayesian estimates for finite population proportions in multinomial problems. To do this, we consider a three-stage hierarchical Bayesian model. For prior, we use Dirichlet density to model each cell probability in each cluster. Our method does not require complicated computation such as Metropolis-Hastings algorithm to draw samples from each density of parameters. We draw samples using Gibbs sampler with grid method. We apply this algorithm to a couple of simulation data under three scenarios and we estimate the finite population proportions using two kinds of approaches We compare results with the point estimates of finite population proportions and their standard deviations. Finally, we check the consistency of computation using differen samples drawn from distinct iterates.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.755-764
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• 2006

Most graphical methods for categorical data can describe the structure of data and represent a measure of association among categorical variables. Among them the polyhedron plot represents sequential relationships among hierarchical log-linear models for a multidimensional contingency table. This kind of plot could be explored to describe the differences among sequential models. In this paper we suggest graphical methods, containing all the information, that reflect the relationship among all log-linear models in a certain hierarchical structure. We use the ideas of a correlation diagram.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1111-1113
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• 1999

This paper presents a algorism for evaluating contingency case power wheeling effects using Monte-Carlo simulation The effects of wheeling on generating cost, transmission losses, and system security are considered. For a specific operating condition, the effects are quantified by the sensitivity of specific quantities of interest with respect to wheeling level. This model is utilized within a Monte-Carlo simulation to calculate probability distribution functions of the incremental effects of wheeling on operating cost, transmission losses, and system security. The model and solution methods are applied on a IEEE RTS-96 system power system and the results are presented.