• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.1013-1021
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• 2003

Huffer and Park (2002) proposed a chi-squared test for multivariate structure. Their test detects the deviation of data from mutual independence or multivariate normality. We will compute the Rao-Robson chi-squared version of the test, which is easy to apply in practice since it has a limiting chi-squared distribution. We will provide a self-contained argument that it has a limiting chi-squared distribution. We study the accuracy in finite samples of the limiting distribution. We finally compare the power of our test with those of other popular normality tests in an application to a real data.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.137-144
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• 2005

In $I{\times}J$ incomplete contingency tables, the test of independence proposed by Chen and Fienberg(1974) uses $I{\times}J-1$ instead of (I-1)(J-1) degrees of freedom without providing much of an increase in the value of the test statistic. For these reasons, Chen and Fienberg tests are expected to have less power. New Wald test statistic related to the part of Chen and Fienberg test statistic is proposed using delta method. These two tests are compared through Monte Carlo studies.

• 한국데이터정보과학회:학술대회논문집
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• 2003.05a
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• pp.121-126
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• 2003

In this paper, we consider two-components system which the lifetimes follow bivariate pareto model with censored data. We develop large sample tests for testing independence between two-components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.1
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• pp.26-38
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• 2020

A statistical test was carried out on the IID (Independently and Identically Distributed) assumption of the AM (Annual Maxima) data used to estimate the design wave height. The test was divided into independence (randomness) test and homogeneity test, and each test was conducted on AM data of 210 and 310 stations in coastal and inner coastal grids in typhoon and non-typhoon (monsoon) conditions. As a result of the independence test, the rejection ratios of the test are in the range of 1.8~5.3% and 1.4~6.0% for the non-typhoon and typhoon data sets, respectively. On the other hand, in the distribution difference test of typhoon data and nontyphoon data, the same distribution hypothesis was found to be rejected in the range of 47~79% according to the test method for both coastal grid and inner coastal grid. Therefore, in estimating design wave height by extreme value analysis, the estimation process by dividing the typhoon and non-typhoon data is appropriate.

• Korean Journal of Child Studies
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• v.16 no.1
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• pp.49-64
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• 1995

The purpose of this study was to investigate differences in social play, cognitive play, and social-cognitive play patterns as related to young children's field independence-dependence cognitive styles. Sixteen field independent and sixteen field dependent children were selected from a group of 79 young children with the use of Preschool Embedded Figures Test(PEFT). Their social play, cognitive play, and social-cognitive play patterns were observed. The data collected for this study were analyzed by using SPSS/$PC^+$; frequency, percentage and ${\chi}^2$ test. The results of this study were that (1) difference of social play patterns as related to young children's field independence-dependence cognitive styles was not found, (2) differences were found in cognitive play patterns as related to young children's field independence-dependence cognitive styles, and (3) differences were found in social-cognitive play pattern as related to young children's field independence-dependence cognitive styles.

• Korean Journal of Human Ecology
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• v.17 no.4
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• pp.575-588
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• 2008

The research is find out the importance of psychological separation of high school students and the effects of this separation from their parents on depression. The data were collected boys(108) and girls(120) second-grade high school students in Jeonbuk area and analyzed Independent-Samples T-test, ANOVA, Pearson's correlation in use of SPSS WIN 11.5 program. The main results are as follows.: 1, Psychological separation from farther was that girls were higher in attitudinal independence than boys. Psychological separation from mother was that boys were higher in functional, emotional independence than girls. There was no significant differences in depression between boys and girls. 2. In the relation between psychological separation from father and depression, girls showed negative correlation attitude independence and both of boys and girls showed positive correlation in conflictual independence. In the relation between psychological separation from mother and depression, boys showed negative correlation in attitude independence and girls showed negative correlation in functional, attitudinal independence and both of boys and girls showed positive correlation in conflictual independence. 3. Psychological separation from father by the level of depression was related attitudinal, conflictual independence for girls and was related conflictual independence for boys. Psychological separation from mother by the level of depression was related functional, attitudinal, conflictual independence for girls and was related attitudinal, conflictual independence for boys. Finally, the more severe depression was related higher conflict independence from their parents.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.521-529
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• 2005

In this paper, we consider a bootstrap method to the 'row and column effects model' (RC model) to analyze a contingency table with ordered variables. We propose a bootstrap procedure for testing of independence, equality of intervals, and goodness of fit in the RC model. A real data example is included.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.257-268
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• 1998

Many epidemiological studies investigate whether an association exists between a binary risk factor X and a binary response variable Y. They analyse whether an observed association between X and Y persists when the level of another factor Z that might influence the association is controlled. This involves testing conditional independence of X and Y controlling for Z. The Mantel-Haenszel test is most widely used to test conditional independence for sparse tables. But if the association between X and Y varies along the levels of Z, Mantel-Haenszel test has a low power problem. In this study, we propose an alternative test procedure which overcomes the low power problem in that case. We find out the null distribution of the alternative test statistic and compare its performance with the Mantel-Haenszel test by simulation.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.493-505
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• 2010

Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.207-215
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• 2017

In this paper we study pooling effects in Bayesian testing procedures of independence for contingency tables from small areas. In small area estimation setup, we typically use a hierarchical Bayesian model for borrowing strength across small areas. This techniques of borrowing strength in small area estimation is used to construct a Bayes test of independence for contingency tables from small areas. In specific, we consider the methods of direct or indirect pooling in multinomial models through Dirichlet priors. We use the Bayes factor (or equivalently the ratio of the marginal likelihoods) to construct the Bayes test, and the marginal density is obtained by integrating the joint density function over all parameters. The Bayes test is computed by performing a Monte Carlo integration based on the method proposed by Nandram and Kim (2002).