• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.155-162
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• 2017

In this paper we propose influence measures for two basic goodness-of-fit statistics, the coefficient of determination $R^2$ and test statistic F in the linear regression model using the deletion method. Some useful lemmas are provided. We also express the influence measures in terms of basic building blocks such as residual, leverage, and deviation that showed them as increasing function of residuals and a decreasing function of deviation. Further, the proposed measure reduces computational burden from O(n) to O(1). As illustrative examples, we applied the proposed measures to the stackloss data sets. We verified that deletion of one or few influential observations may result in big change in $R^2$ and F-statistic.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.317-325
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• 2010

In this paper, we develop four modified empirical distribution function (EDF) type tests using approximate maximum likelihood estimators for the half-logistic distribution based on multiply Type-II censored samples. We also propose modified normalize sample Lorenz curve polt and new test statistics. We compare the above test statistics in the sense of the power for various censored samples. We present an example to illustrate this method.

• Journal of the Korean Society of Safety
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• v.35 no.3
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• pp.105-115
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• 2020

This study compares the difference of fit factors (FF) and visual acuity according to masks and eyeglasses preferences for 54 participants. We the precautions and behaviors of discomfort when wearing masks of eyewear wearers. Contact lens discomfort and priority action of complaints was investigated Glasses fitting factors is Optical Center Height(OH), Vertex Distance(VD) and Pantoscopic Angle(PA). We measured those factors and expressed by the ratio of standard point and change point. Quantitative fit factor was measured by Portacount Pro+ 8038. Also, we selected to 6 exercises among 8 exercises OSHA QNFT (Quantitative Fit testing) protocol to measure the fit factors. The pass/ fail criterion of FF was set at 100. Visual acuity(VA) test chart is developed by Chunsuk Han was used, Descriptive statistics was performed. Descriptive statistics(SAS ver 9.2), it is used geometric means, Wilcoxon analysis(P=0.05) When wearing the mask preferentially, fit factor(FF) was high according to the step of glasses fitting parameter. on the other hand, when the glasses first choice, the visual acuity(VA) was high. there was no significant difference. In the case of fit factor (FF), mask first choice/ glasses first choice is OH (p=0.671/ p=0.332), VD (p=0.602/ p=0.571) and PA (p=0.549/ p=0.607). Visual acuity (VA), mask first choice/ glasses first choice is OH (p=0.753/ p=0.386), VD (p=0.815/ p=0.557) and PA (p=0.856/ p=0.562). The workers of workplace and office chose glasses but occupational health workers and students chose mask. In case of discomforts, it was suggested to remove the mask and tolerate discomforts. The main discomforts and usual action of lens were dryness, hyperemia, foreign body sensation, ophthalmodynia, decreased vision and glasses wearing. Therefore, it is necessary to develop a mask wearing method education program considering glasses fitting and develop a hybrid model that minimizes inconvenience when wearing glasses and a mask at the same time.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.290-302
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• 2015

The study purpose was to test the validity and reliability of the Korean version of the Revised Stress Appraisal Measure (RSAM) to assess stress appraisal in undergraduate students. Internal consistency reliability, construct and criterion validity were calculated using IBM SPSS Statistics 21 and AMOS 21 program. Survey data were collected from a convenience sample of 296 undergraduate students enrolled in five universities in G city and C area, South Korea. The Korean version of RSAM categorized into 5 factors explaining 68.4% of the total variance. The model of five subscales was validated by confirmatory factor analysis (p<.001, Goodness of Fit Index, Adjusted Goodness of Fit Index, Normed Fit Index, Comparative Fit Index >.08, Root Mean Square Error of Approximation=.056). In criterion validity, the scores for the scale were significantly correlated with the Perceived Stress Scale-Korean. Cronbach's alpha coefficient for the 19 items was .73~.89. The Korean RSAM showed satisfactory construct and criterion validity and reliability. Thus it may be an appropriate instrument for measuring stress appraisal in Korean university students.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1271-1284
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• 2011

The entropy-based test of fit for the inverse Gaussian distribution presented by Mudholkar and Tian(2002) can only be applied to the composite hypothesis that a sample is drawn from an inverse Gaussian distribution with both the location and scale parameters unknown. In application, however, a researcher may want a test of fit either for an inverse Gaussian distribution with one parameter known or for an inverse Gaussian distribution with both the two partameters known. In this paper, we introduce tests of fit for the inverse Gaussian distribution based on the Kullback-Leibler information as an extension of the entropy-based test. A window size should be chosen to implement the proposed tests. By means of Monte Carlo simulations, window sizes are determined for a wide range of sample sizes and the corresponding critical values of the test statistics are estimated. The results of power analysis for various alternatives report that the Kullback-Leibler information-based goodness-of-fit tests have good power.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.193-209
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• 2017

The power Lindley distribution with some of its properties is considered in this article. Maximum likelihood, least squares, maximum product spacings, and Bayes estimators are proposed to estimate all the unknown parameters of the power Lindley distribution. Lindley's approximation and Markov chain Monte Carlo techniques are utilized for Bayesian calculations since posterior distribution cannot be reduced to standard distribution. The performances of the proposed estimators are compared based on simulated samples. The waiting times of research articles to be accepted in statistical journals are fitted to the power Lindley distribution with other competing distributions. Chi-square statistic, Kolmogorov-Smirnov statistic, Akaike information criterion and Bayesian information criterion are used to access goodness-of-fit. It was found that the power Lindley distribution gives a better fit for the data than other distributions.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.347-358
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• 1996

A new test for goodness-of-fit is presented. It is a modification of a test of LaRiccia (1991). These tests are applicable to continuous lo-cation/scale models. The new test statistic is based on a few selected order statistics taken from the sample, while the LaRiccia test is based directly on the full sample. Each test embeds the hypothesized model in a larger linear model and proceeds to test the goodness-of-fit hy-pothesis by testing the coefficients of this linear model appropriately. The general theory is presented. The tests are compared via computer simulation to a related test of Ali and Umbach (1989) for distributions that could be used as lifetime models. An important aspect of all these tests is that only standard $X_2$ tables are used. Selection of the spacings of the order statistics is discussed.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.125-134
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• 2014

Kullback-Leibler (KL) information is a measure of discrepancy between two probability density functions. However, several nonparametric density function estimators have been considered in estimating KL information because KL information is not well-defined on the empirical distribution function. In this paper, we consider the KL information of the equilibrium distribution function, which is well defined on the empirical distribution function (EDF), and propose an EDF-based goodness of fit test statistic. We evaluate the performance of the proposed test statistic for an exponential distribution with Monte Carlo simulation. We also extend the discussion to the censored case.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.411-424
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• 2011

The studies of congruence in organizational research have explored the concepts such as person-job fit person-organization fit, or person-environment fit. The relevant studies dealt with the fit level as an important influencing factor on the performance. In particular, researchers have agreed that employees can be motivated by the high level fit of person-organization. However, few research developing an alternative methodological approach has been done. For the purpose mentioned above the statistics like D, |D| or $D^2$ and the Q values such as Q(the correlation between two sets of interval measures) or $Q_r$(the correlation between two rankings) have been conventionally adopted in spite of numerous methodological problems. In general, these traditional indices such as difference scores, or Q values, are nondirectional and add an extra weight to differences of lager magnitude. Therefore, Edwards (1993) introduced the polynomial regression and the response surface analysis to overcome flaws with conventional approaches. However, the method-ological approaches did not reflect the profile characteristics of person-organizational value fit and wouldn't be a proper solution for the fit level of person-organization value maximizing performance. Hence, this paper investigates alternative methodological approaches, the multivariate polynomial regression and the multiple response surface analysis, to avoid the problems issued from conventional ways.

• Journal of the Korean Mathematical Society
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• v.47 no.6
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• pp.1137-1146
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• 2010

In this paper, we study the divergence based goodness of fit test for partially observed sample from diffusion processes. In order to derive the limiting distribution of the test, we study the asymptotic behavior of the residual empirical process based on the observed sample. It is shown that the residual empirical process converges weakly to a Brownian bridge and the associated phi-divergence test has a chi-square limiting null distribution.