• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.853-864
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• 2002

In the analysis of categorical data subject to misclassification errors, the observed cell proportions are adjusted by a misclassification probabilities and estimates of variances are adjusted accordingly. In this case, it is important to determine the extent to which misclassification probabilities are homogeneous within a population. This paper considers methods to evaluate the power of chi-squared tests for homogeneity with complex survey data subject to misclassification errors. Two cases are considered: adjustment with homogeneous misclassification probabilities; adjustment with heterogeneous misclassification probabilities. To estimate misclassification probabilities, logistic regression method is considered.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.4
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• pp.107-117
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• 2014

This study tests homogeneity and performs multiple comparison analysis among treatment levels of each factor group through t-test by materials and analysis of variance by structural type and service period. For that descriptive statistical analysis is performed for static and dynamic response characteristics and their ratios of calculated versus measured values based on a good many safety assessment reports for bridges. Homogeneity and post hoc test based on descriptive statistical analysis provide the measures for homogeneity identification among comparison groups in addition to the statistical reference values such as central tendency, variation and shape. This study is expected to be valuable for structural integrity assessment and design by comparing the measured and calculated values with the reference values for the homogeneous group identified, which can help the engineers review the adequacy of the values and put the group database to practical use.

• Journal of Korean Academy of Nursing
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• v.28 no.4
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• pp.941-957
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• 1998

The purpose of this study was to use meta-analysis to analyze result of 17 studies which investigated the effects of integrated programs, and 11 studies which examined the effects of exercise programs on pain, depression, and disability. The 28 studies analyzed in this work were selected from the following sources. MEDLINE Search, bibliographies of related studies, main academic journals of nursing in Korea, and journals on arthritis issues. For the analysis of the data, homogeniety of effect sizes which were calculated based on data in the 28 studies was tested and its average effect size was computed by using meta analysis software package which was developed by Song(1992, 1998). The results can be summarized as follows : 1) Homogeneity tests were conducted on integrated programs on pain. In the prelimiary homogeneity tests on effect size of all 17 studies, no homogeneity was found. When homogeneity tests on the effect size of the remaining 15 studies were performed, excluding two studies which had extremely larger effect size compared to other studies, the 15 studies were found to be homogeneous(Q=16.38, p=.23). The obtained average effect size, D(Mean Standardized Difference Between Means), was .25. When homogeneity tests on effect size on pain was conducted for the excercise programs, effect size for all nine studies were found to be homogeneous (Q=7.42, p=.49) and the average effect size D=.30. Therefore, Hypothesis 1 was rejected from the results, that an average effect size of the integrated programs on pain was not significantely different from that of the exercise programs on pain. 2) Since only two studies investigated the effect of exercise programs on depression, comparison between the average effect size of integrated programs and that of exercise programs on depression could not be conducted, and hypothesis 2 could not be tested. Thereby, only the average effect size of integrated programs on depression was obtained. Eight studies were tested to be positive on the homogeneity of effect sizes(Q=18.31, p=.02) at $\alpha$<.01 and its average effect size was D=.11. 3) For the analysis of integrated program on disability, 13 studies, except for four which had an extremely large effect size compared to the others were found to be homogeneous at $\alpha$<.01 (Q=22.30, p=.04) and the average effect size on disability was D=.16. For analysis of the exercize programs on disability, eight studies, except for one which had an extremely large effect size compared to others, were found to be homo geneous(Q=7.87, p=.34) and the average effect size on disability was D=.60. Therefore, Hypothesis 3 was accepted from the results that an average effect size of exercise programs on disability was significantly larger than that of integrated programs on disability.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.605-614
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• 2008

Oh (2008) has proposed the one-sided likelihood ratio test of the equality of two agreement measures. However the use of this test may be limited since the computations of test statistic and critical value are not easy. We propose a test for comparing two dependent agreements using some well known tests for marginal homogeneity, for instance, Bhapkar test, Stuart-Maxwell test. Data obtained from 2008 world figure skating championship ladies single is analyzed for illustration purposes.

• Journal of the Korean Statistical Society
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• v.17 no.2
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• pp.61-80
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• 1988

For testing homogeneity of scale parameters aginst ordered alternatives, some nonparametric test statistics based on pairwise ranking method are proposed. The proposed tests are distribution-free. The asymptotic distributions of the proposed statistcs are also investigated. It is shown that the Pitman efficiencies of the proposed rank tests are the same as those of the corresponding two-sample rank tests in the scale problem. A small-sample Monte Carlo study is also performed. The results show that the proposed tests are robust and efficient.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.777-781
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• 2010

Yates' continuity correction of the chi-squared test for testing the homogeneity of two binomial proportions in $2{\times}2$ contingency tables is developed to lower the value of the test statistic slightly. The effect of continuity correction is expected to decrease as the sample size increases. However, in extremely unbalanced $2{\times}2$ contingency tables, we find some cases where the effect of continuity correction is eccentric and is larger than expected. In such cases, we conclude that the chi-squared test with continuity correction should not be employed as a test statistic in both asymptotic tests and exact tests.

• Journal of Korean Society for Quality Management
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• v.45 no.3
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• pp.447-462
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• 2017

Purpose: This study aims to develop distributable samples that can be used for proficiency testing to verify the ability of the testing laboratory to perform high temperature and low temperature tests. Method: In this study, the temperature-resistance characteristics of the NTC thermistor were used to develop samples. The homogeneity and stability of samples were examined according to the proficiency testing requirements. Results: Thirty samples with homogeneity and stability were developed and used for the proficiency testing. Thus, it was possible to distinguish between the test laboratories that showed satisfactory results and those that did not. Conclusion: It was the first time to develop samples that can be used for proficiency testing in high temperature and low temperature tests. and it was proved that the proficiency test program can be operated using the characteristics of NTC thermistor.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.433-444
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• 2016

When we observe binary responses in a cluster (such as rat lab-subjects), they are usually correlated to each other. In clustered binomial counts, the independence assumption is violated and we encounter an extra-variation. In the presence of extra-variation, the ordinary statistical analyses of binomial data are inappropriate to apply. In testing the homogeneity of proportions between several treatment groups, the classical Pearson chi-squared test has a severe flaw in the control of Type I error rates. We focus on modifying the chi-squared statistic by incorporating variance inflation factors. We suggest a method to adjust data in terms of dispersion estimate based on a quasi-likelihood model. We explain the testing procedure via an illustrative example as well as compare the performance of a modified chi-squared test with competitive statistics through a Monte Carlo study.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.151-158
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• 1999

Distribution-free tests are proposed for AB/BA 2*2 cross-over design data based on placements introduced by Orban and Wolfe(1992). In this paper we suggest the homogeneity test or carry-over effects and also suggest the test for direct effects and the test for period effects under the same carry-over effects. The properties such as iterative asymptotic distribution for the proposed tests are discussed.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1547-1555
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• 2017

This paper studies Bayesian test of homogeneity in contingency tables made by discretizing a continuous variable. Sometimes when we are considering events of interest in small area setup, we can think of discretization approaches about the continuous variable. If we properly discretize the continuous variable, we can find invisible relationships between areas (groups) and a continuous variable of interest. The proper discretization of the continuous variable can support the alternative hypothesis of the homogeneity test in contingency tables even if the null hypothesis was not rejected through k-sample tests involving one-way ANOVA. In other words, the proportions of variables with a particular level can vary from group to group by the discretization. If we discretize the the continuous variable, it can be treated as an analysis of the contingency table. In this case, the chi-squared test is the most commonly employed method. However, further discretization gives rise to more cells in the table. As a result, the count in the cells becomes smaller and the accuracy of the test becomes lower. To prevent this, we can consider the Bayesian approach and apply it to the setup of the homogeneity test.