• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.967-976
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• 1999

In this paper we study the Hellinger distance based goodness-of-fit tests that are analogs of likelihood ratio tests. The minimum Hellinger distance estimator (MHDE) in normal models provides an excellent robust alternative to the usual maximum likelihood estimator. Our simulation results show that the Hellinger deviance test (Simpson 1989) based goodness-of-fit test is robust when data contain outliers. The proposed hellinger deviance test(Simpson 1989) is a more direcct method for obtaining robust inferences than an automated outlier screen method used before the likelihood ratio test data analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.119-128
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• 2000

This study develops the pay satisfaction questionnaire for Korean employees. Based upon the review of previous studies, 16 questionnaire items are developed. Exploratory factor analysis results in a modified measurement through item deletion, item-to-dimension reassignment, and dimension combination. The measurement model was good fit assessed by overall fit measures(GFI; goodness of fit index, AGFI; adjusted goodness of fit index, RMR; root mean square residual) criteria, lambda score, and squared multiple correlation with confirmatory factor analysis. Implication of this work for future theoretical and empirical development are suggested.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.229-240
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• 2002

Whether to use linear or quadratic model in the analysis of regression data is one of the important problems in classical regression model and measurement error model (MEM). In MEM, four goodness of fit test statistics are available In solving that problem. Two are from the derivation of estimators of quadratic MEM, and one is from that of the general $k^{th}$-order polynomial MEM. The fourth one is derived as a variation of goodness of fit test statistic used in linear MEM. The purpose of this paper is to find the most powerful test statistic among them through the small-scale simulation.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.607-617
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• 2012

The goodness-of-fit test for multivariate normal distribution is important because most multivariate statistical methods are based on the assumption of multivariate normality. We propose goodness-of-fit test statistics for multivariate normality based on the modified squared distance. The empirical percentage points of the null distribution of the proposed statistics are presented via numerical simulations. We compare performance of several test statistics through a Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.187-194
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• 2014

We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.955-969
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• 2003

The classical Fourier analysis, which is the typical frequency domain approach, is used to detect periodic trends that are of the sinusoidal shape in time series data. In this article, using a sequence of periodic step functions, describes an adaptive Fourier series where the patterns may take general periodic shapes that include sinusoidal as a special case. The results, which extend both Fourier analysis and Walsh-Fourier analysis, are applies to investigate the shape of the periodic component. Through the real data, compare the goodness-of-fit of the model using two methods, the adaptive Fourier method which is proposed method in this paper and classical Fourier method.

• Journal of Families and Better Life
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• v.27 no.6
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• pp.229-242
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• 2009

This study investigates how bioecological variables affect the child's multiple intelligence through independent and interactional ways. The subjects of this study were 147 pairs of 5-year-old children and their mothers, and the Project Spectrum was employed to measure multiple intelligences. Each mothers was asked to answer a questionnaire on her child's temperament, her maternal parenting style, 'goodness of fit' and 'the fit of child's intelligence'. Data were analyzed using a factor analysis and a hierarchical multiple regression with SPSS WIN 15.0. The main findings were as followings; First, 'the goodness of fit' to the child's temperament moderated the effect of a maternal parenting style that would foster child's dependency on the mathematical intelligence through interaction. 'The fit of child's intelligence' also moderated the effect of maternal positive parenting style to the child's mathematical intelligence. Second, in language intelligence, girls were more verbally intelligent than boys. In that regard, because the sex variable entails a combination of both inherent attribute and social-cultural effects, that result can be interpreted as an interaction between the individual and the environment. Lastly, a maternal parenting style that would foster child's dependency moderated the effect of the child's regular temperament on interpersonal intelligence. This means that the child's regular temperament can be a protective factor for the negative effect of a maternal parenting style that would foster child's dependency This study suggests that interactional factors such as 'goodness of fit' should be considered in studies involving children.

• Journal of Families and Better Life
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• v.22 no.4
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• pp.29-41
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• 2004

The patterns of mother-child personality match were investigated in the study. Further, the impact of goodness-of-fit between mother′s and child′s personality on maternal childrearing behaviors, child′s self-esteem, and child′s emotional intelligence was explored. The participants of this study were 1,060 fifth graders and their mothers from four different cities(Seoul. Suwon, Daejon, and Daegu). Six patterns of mother-child personality match were derived through cluster analysis and discriminant analysis. The most harmonious pattern in which maternal childrearing behavior was positive and child′s self-esteem and emotional intelligence were high appeared between mothers and children with high "stability" and "superiority" The least harmonious pattern was shown for the mothers with low "responsibility" and "reflectiveness" and high "dominance′and "sociability", and the children with low "stability" and "superiority".

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.489-498
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• 1998

The influence of observations the on the goodness-of-fit test in maximum likelihood factor analysis is investigated by using the local influence method. under an appropriate perturbation the test statistic forms a surface. One of main diagnostics is the maximum slope of the perturbed surface the other is the direction vector cor-responding to the curvature. These influence measures provide the information about jointly influence measures provide the information about jointly influential observations as well as individ-ually influential observations.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.643-653
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• 2013

The most important procedure in frequency analysis is to determine the appropriate probability distribution and to estimate quantiles for a given return period. To perform the frequency analysis, the goodness-of-fit tests should be carried out for judging fitness between obtained data from empirical probability distribution and assumed probability distribution. The previous goodness-of-fit could not consider enough extreme events from the recent climate change. In this study, the critical values of the modified Anderson-Darling test statistics were derived for 3-parameter Weibull distribution and power test was performed to evaluate the performance of the suggested test. Finally, this method was applied to 50 sites in South Korea. The result shows that the power of modified Anderson-Darling test has better than other existing goodness-of-fit tests. Thus, modified Anderson-Darling test will be able to act as a reference of goodness-of-fit test for 3-parameter Weibull model.