• Journal of applied mathematics & informatics
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• v.1 no.1
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• pp.43-48
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• 1994

There are some difficulties in applying the Pearson's Chi-Square Test for the continuous distribution. The problems include how to form class intervals for the test of fit how to employ in the test when the estimators of parameters are obtained from the ungrouped sample so on. In order to solve these problems we use the generalized minimum Chi-Square technique which is a test free of the complications associated with the Peason's Chi-Square test. This paper show how to apply the goodness of fit tests based on generalized minimum Chi-Square technique to the extreme values.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.375-382
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• 1999

Linear-by-linear association models are commonly used to analyze ordered categorical data. To fit these models appropriate scores need to be chosen. In this paper we perform sensitivity analyses in two-way contingency tables to investigate the effect of scores on goodness-of-fits and on tests of significance. In addition we show that the best score which yields the best fit of data can be selected based on the sensitivity analysis results.

• The Journal of Korean Academic Society of Nursing Education
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• v.8 no.1
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• pp.61-71
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• 2002

purpose : The purpose of this study was to find out the influencing factors of smoking-cessation behavior of patients with coronary heart disease and to suggest the model of smoking-cessation behavior which was based on the relationship between influencing factors and then to test its fitness empirically. method : This study was based on the Theory of Reasoned Action and a hypothetical model was constructed with fifteen paths in consideration of main predictive factors of smoking-cessation behavior such as biological factor, disease-related characteristics, self-efficacy, supportive factor, environmental factor, disease-related perception factor, intention-to-quit, and psychological factor. The validity of a smoking- cessation model was tested to 264 patients with coronary heart disease by using SPSS 8.0 and Window LISREL 8.12a. results : 1. Seven of the 15 paths of smoking-cessation behavior proved to be significant. 2. The final model excluded three paths in the hypothetical model was demonstrated to be improved by $x^2$=44.31 (df=38, p=.22), Goodness of Fit Index (GFI)=.98, Adjusted Goodness of Fit Index (AGFI)=.96, Non-Normed Fit Index(NNFI)=1.00, Normed Fit Index(NFI)=1.00, and Root Mean Square Residual(RMR)=.24. 3.The smoking-cessation behavior was influenced directly by biological factor, self-efficacy, supportive factor, environmental factor, intention-to-quit, and psychological factor. The smoking-cessation behavior was accounted for 82% of variance by these factors. conclusion : although the adolescents' smoking behavior can be predicted by only smoking intention, it is hard to predict the adults' smoking-cessation behavior by only this factor. Therefore, intention-to-quit, self-efficacy, supportive factor should be improved because these are promotive factors for smoking-cessation behavior. Biological factor, environmental factor, and psychological factor are inhibitive factors, so nicotine replacement therapy is helpful to the high nicotine-dependents, and ex-smokers avoid other smokers in their environment and also patients should learn and practice the stress coping-skills.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.507-516
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• 2011

Comparative studies on generalized binomial models (Moon, 2003; Ng, 1989; Paul, 1985; Kupper and Haseman, 1978; Griffiths, 1973) are restrictive in that the models compared are rather limited and MSE of the estimates is the only measure considered for the model adequacy. This paper is aimed to report simulation results which provide possible guidelines for selecting a proper model. We examine Pearson type of goodness-of-fit statistic to its degrees of freedom and AIC for the overall model quality. MSE and Bias of the individual estimates are also considered as the component fit measures. Performance of some models varies widely for a certain range of the parameter space while most of the models are quite competent. Our evaluation shows that the Extended Beta-Binomial model (Prentice, 1986) turns out to be particularly favorable in the point that it provides consistently excellent fit almost all over the values of the intra-class correlation coefficient and the probability of success.

• Health Policy and Management
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• v.23 no.4
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• pp.415-426
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• 2013

Background: This study was aim to identify the specific words and to develop the scale for the public health center (PHC) image. Methods: We collected 824 words from the previous studies and by open questions and reduced them by 77 words, then which were rated properly by 355 citizens of Seoul. We examined explanatory factor analysis for 69 words, and examined content validity test and confirmatory factor analysis (CFA) for the image structures (4 factors and 16 words). And then we developed the image questionnaire using them through council. We conducted a survey and retested the PHC image scales as the measuring tool targeting 2,000 persons, and compared the inexperience and experience persons for PHC usage. Results: The image structures were consisted of 4 factors and 16 words such as 'trustworthiness' (warm, exemplary, faithful, service-mindedness, beneficial to health), 'fairness' (honesty, clear, consistent, ruled), 'development possibility' (changing, goal-directed, developmental, propulsive), and 'flexibility' (not authoritative, not perfunctory, not rigid) in total. Cronbach's ${\alpha}$ values of all factors were above 0.7. As a result of CFA, model fit indexes yielded satisfactory results (root mean square error of approximation [RMSEA] 0.049, goodness of fit index [GFI] 0.937, and adjusted goodness of fit index [AGFI] 0.912). According to the result of retest for measuring tool by using other samples, Cronbach's ${\alpha}$ values were above 0.8, and model fit indexes yielded satisfactory results (RMSEA 0.059, GFI 0.952, AGFI 0.933). RMSEAs of the inexperiences and the experiences were each 0.59, 0.68. Conclusion: A reliable, valid, and generalizable scale was created for PHC image.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.611-622
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• 2013

Mudholkar and Tian (2002) proposed an entropy-based test of fit for the inverse Gaussian distribution; however, the test can be applied to only the composite hypothesis of the inverse Gaussian distribution with an unknown location parameter. In this paper, we propose an entropy-based goodness-of-fit test for an inverse Gaussian distribution that can be applied to the composite hypothesis of the inverse Gaussian distribution as well as the simple hypothesis of the inverse Gaussian distribution with a specified location parameter. The proposed test is based on the probability integration transformation. The critical values of the test statistic estimated by simulations are presented in a tabular form. A simulation study is performed to compare the proposed test under some selected alternatives with Mudholkar and Tian (2002)'s test in terms of power. The results show that the proposed test has better power than the previous entropy-based test.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1117-1117
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• 2016

Journal of the Korean Data & Information Science Society, Vol. 24, No. 6, 1465-1475, 2013 (http://dx.doi.org/10.7465/jkdi.2013.24.6.1465). This article has been retracted at the research ethics committee.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.687-694
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• 1999

The goodness of fit statistics of normality plots are obtained using the Receiver Operating Characteristic(ROC) method. This work is intended to compare with Shapiro-Wilk W statistic. Wel will use and discuss an accuracy of the test and the best cut-off value which minimizes the sum of the type I and II error probabilities.

• Proceedings of the Safety Management and Science Conference
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• 2007.04a
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• pp.335-346
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• 2007

This paper introduces reliability stress screening(RSS) for electronic hardware and components. This study also shows reliability centered maintenance(RCM), and reliability growth models. Moreover, this paper presents goodness-of-fit tests and estimation methods of power law model.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.61-71
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• 1996

Kim and Song(1995)과 Kim and Lee(1996)는 하나의 이지공변량(binary covariate)을 갖는 가산위험모형(additive risk model)의 적합도검정법(goodness-of-fit test)을 제안했다. 전자는 모수의 가중추정량들의 차에 기초한 검정법이며 후자는 마팅게일잔차(martingale residual)에 기초한 검정법이다. 본 논문에서는 모의실험을 통하여 두 검정법을 비교하였다.