• Communications for Statistical Applications and Methods
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• 제16권4호
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• pp.697-705
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• 2009

The Pearson chi-squared statistic or the deviance statistic is widely used in assessing the goodness-of-fit of the generalized linear models. But these statistics are not proper in the situation of continuous explanatory variables which results in the sparseness of cell frequencies. We propose a goodness-of-fit test statistic for the cumulative logit models with ordinal responses. We consider the grouping of a dataset based on the ordinal scores obtained by fitting the assumed model. We propose the Pearson chi-squared type test statistic, which is obtained from the cross-classified table formed by the subgroups of ordinal scores and the response categories. Because the limiting distribution of the chi-squared type statistic is intractable we suggest the parametric bootstrap testing procedure to approximate the distribution of the proposed test statistic.

• Communications for Statistical Applications and Methods
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• 제26권2호
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• pp.191-203
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• 2019

The problem of examining how well an assumed distribution fits the data of a sample is of significant and must be examined prior to any inferential process. The observed failure time data of items are often not wholly available in reliability and life-testing studies. Lowering the expense and period associated with tests is important in statistical tests with censored data. Goodness-of-fit tests for perfect data can no longer be used when the observed failure time data are progressive Type II censored (PC) data. Therefore, we propose goodness-of-fit test statistics and a graphical method based on generalized Lorenz curve for PC data from a location-scale distribution. The power of the proposed tests is then assessed through Monte Carlo simulations. Finally, we analyzed two real data set for illustrative purposes.

• Communications for Statistical Applications and Methods
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• 제19권4호
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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.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.233-238
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• 2003

Goodness of fit test statistics based on the information discrepancy have been shown to perform very well (Vasicek 1976, Dudewicz and van der Meulen 1981, Chandra et al 1982, Gohkale 1983, Arizona and Ohta 1989, Ebrahimi et al 1992, etc). Although the test is well defined for the non-censored case, censored case has not been discussed in the literature. Therefore we consider a goodness of fit test based on the partial Kullback-Leibler(KL) information with the type II censored data. We derive the partial KL information of the null distribution function and a nonparametric distribution function, and establish a goodness of fit test statistic. We consider the exponential and normal distributions and made Monte Calro simulations to compare the test statistics with some existing tests.

• 가정과삶의질연구
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• 제27권6호
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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 the Korean Data and Information Science Society
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• 제25권1호
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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.

• 산업경영시스템학회지
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• 제23권54호
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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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• 제8권2호
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• pp.483-497
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• 2001

When one fits a parametric density function to a data set, it is usually advisable to test the goodness of the postulated model. In this paper we study the nonparametric tests for testing the null hypothesis against general alternatives, when the null hypothesis specifies the density function up to unknown parameters. We modify the test statistic which was proposed by the first author and his colleagues. Asymptotic distribution of the modified statistic is derived and its performance is compared with some other tests through simulation.

• International Journal of Reliability and Applications
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• 제10권1호
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• pp.59-62
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• 2009

We comment on a new testing procedure for testing exponentiality against different ageing classes. We show that the proposed test is inappropriate at least for two alternatives. We point out the subtle flaw in their argument.

• 한국콘텐츠학회논문지
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• 제15권3호
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• pp.290-302
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• 2015

본 연구의 목적은 대학생들을 대상으로 수정된 스트레스 평가 도구(Revised Stress Appraisal Measure, RSAM)를 우리나라 실정에 맞게 번역하고, 타당도와 신뢰도를 검증하는 것이다. IBM SPSS Statistics 21과 AMOS 21 program을 이용하여 내적 일관성 신뢰도, 구성타당도, 준거타당도 검사를 하였다. 자료 수집은 G시와 C 지역 소재의 5개 대학교에 재학 중인 296명의 대학교 4학년 학생을 임의로 표출하였다. 한국어판 RSAM은 5개 요인으로 분류되었으며, 전체 변량은 68.4%를 설명하였다. 5개의 하위요인은 확증적 요인분석에 의해 타당성이 입증되었다(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). 준거타당도에서, 척도의 점수는 한국어판 Perceived Stress Scale (PSS)와 유의한 상관관계가 있었다. 신뢰도 계수는 .73에서 .89까지였다. 한국어판 RSAM 은 구성타당도와 준거타당도, 그리고 내적 일관성 신뢰도에서 만족할 만한 것으로 나타났다. 따라서 본 도구는 한국 대학생들의 스트레스 평가를 측정하는데 적합한 도구가 될 수 있을 것이다.