• Journal of the Korean Statistical Society
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• v.18 no.1
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• pp.38-45
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• 1989

A procedure is considered to the problem of testing whether there exist changes in location at possibly two points in a sequence of independent random variables which are successively drawn from normal population. A test statistics based on modified likelihood ratio is proposed and its asymptotic null distribution is derived through the stochastic process representation. A small sample power comparison is made by Monte Carlo method.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.519-531
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• 2017

We consider goodness-of-fit test statistics for Weibull distributions when data are randomly censored and the parameters are unknown. Koziol and Green (Biometrika, 63, 465-474, 1976) proposed the $Cram\acute{e}r$-von Mises statistic's randomly censored version for a simple hypothesis based on the Kaplan-Meier product limit of the distribution function. We apply their idea to the other statistics based on the empirical distribution function such as the Kolmogorov-Smirnov and Liao and Shimokawa (Journal of Statistical Computation and Simulation, 64, 23-48, 1999) statistics. The latter is a hybrid of the Kolmogorov-Smirnov, $Cram\acute{e}r$-von Mises, and Anderson-Darling statistics. These statistics as well as the Koziol-Green statistic are considered as test statistics for randomly censored Weibull distributions with estimated parameters. The null distributions depend on the estimation method since the test statistics are not distribution free when the parameters are estimated. Maximum likelihood estimation and the graphical plotting method with the least squares are considered for parameter estimation. A simulation study enables the Liao-Shimokawa statistic to show a relatively high power in many alternatives; however, the null distribution heavily depends on the parameter estimation. Meanwhile, the Koziol-Green statistic provides moderate power and the null distribution does not significantly change upon the parameter estimation.

• Journal of the Korean Home Economics Association
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• v.27 no.3
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• pp.133-146
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• 1989

The purpose of this study was to investigate the differences of conjugal power type and conjugal violence level according to social class. This study was also intended to examine the relations between conjugal power type and conjugal violence level. The subjects of this study were 492 high school students in Seoul. Conjugal power was measured with used to measure the conjugal violence level. For the statistical analysis of data, x2-test, Pearson's r, F-test, Duncan's Multiple Range Test and Cronbach's α for reliability were performed. The major results of this study were summarized as follows; 1. There were significant differences according to social class in conjugal power type: The higher social class of the family, the more Syncratic Type were found. And the lower social class of the family, the more Wife Dominant Type were found. 2. There were significant differences according to social class in conjugla violence level: Couples of the lowest class appeared to be more verbal aggression and physical violence. 3. The most severe Husband-to-Wife verbal aggression and physical violence were appeared when the conjugal power type is either Husband Dominant Type or Wife Dominant Type.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.419-432
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• 1996

When interactions are not present in a three-way layout, the lim-iting null distribution of the F statistic for testing main effects when applied to the rank-score transformed data is the same as the limiting null distribution of the usual F statistic when applied to the normal data. The simulation results exhibit that the rank transform test is robust with respect to significance level and powerful for testing main effects in a three-way factorial experiment.

• Journal of Acupuncture Research
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• v.20 no.1
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• pp.144-158
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• 2003

This study was carried out to investigate what kinds of statistical techniques have been used to analyze data from oriental medicine research, For study, 551 original articles which used statistical techniques in their data analysis were selected form the articles published in The journal of Korean Acupuncture & Moxibustion Society(JKAMS) between 1984 to 2002. among them, 122 articles used descriptive statistics while 429 articles used inferential statistics for data analysis. For that 429 articles, t-test (189 articles), analysis fo variance (111 articles), chi-square test (14 articles), correlation (10 articles), regression analysis (4 articles), factor analysis(5 articles), or nonparametric test (23 articles) were chose to analyze the data. Nonparametric approach has substantial power in case data do not meet the assumption of normality. This method is not only easy to use ut also provides measures of the statistical variation of nominal and ordinal scale. This study shows that more and more recent papers use nonparametric test compared to the old articles. nine different statistical software or packages (SAS, SPSS, Statview, Minitab, Sigma plot, ISP, Graphpad prism, Excel, Access) have been used in the articles published JKMAS. High level statistical techniques such as SAS, SPSS, and Statview are user friendly and used most for acupuncture and Moxibustion research. Including tables and plots in an article facilitates understanding family process data from a descriptive standpoint, minimized erroneous statistical conclusions, and clarifies theoretically important relationships among variables. Table and plots have been used 500 and 233 articles, respectively. A computer procedure is proposed and illustrated with statistical packages using SAS, SPSS, Statview and ISP.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.945-957
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• 2009

Repeated measurement data among several treatments with a control is often used in the field of medicine study. In this paper, we suggest a method for comparison of the linear trend of responds followed time among several treatments with a control based on repeated measurement data. First, we estimate slope from each subject and generate samples using the slope estimated previous. And then, we test the difference among treatment with a control by ANOVA F test, Jonckheere-Terpstra test, updated control group procedure using generated samples. Monte Carlo Simulation is adapted to compare the power and experimental significance levels in various configuration.

• IE interfaces
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• v.6 no.1
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• pp.55-65
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• 1993

A nonstandard instrument used in the filed frequently becomes out-of-calibration due to environmental noise, misuse, aging, etc. A substantial amount of loss may result if such nonstandard instrument is used to check product quality and performance. Traditional periodic calibration at the calibration center is not capable of detecting out-of-calibration status while the instrument is in use, and therefore, statistical methods need to be developed to check the status of a nonstandard instrument in the field between calibrations. Developed in this paper is a unified measurement assurance model in which statistical calibration at the calibration center and measurement assurance test in the filed are combined. We developed statistical procedures to detect changes in precision and in the coefficients of the calibration equation. Futher, computational experiments are conducted to evaluate how the power of test varies with respect to the parameters involved. Based upon the computational results we suggest procedures for designing effective measurement assurance tests.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.51-63
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• 2001

We are interested in the conditional independence in sparse $2\tims2\tims$K tables with very rare cell counts. The most popular test is Cochran-Mantel-Haenszel statistic when sample sizes are moderately large enough to guarantee the chi-square approximation. We will consider jackknifing the CMH test and also suggest an approximate normal distribution for the standardized jackknifed CMH statistic. The main focus of this paper is to improve the chi-squared approximation to the CMH test by using the asymptotic normality of the jackknifed CMH test when sample sizes are very sparse but K and N$\infty$. The performance of the proposed jackknifed test, in the sense of significance level control and power, will be compared with that of the CMH test through a Monte Carlo study.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.451-457
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• 2012

Baumgartner et al. (1998) proposed a novel statistical test for the null hypothesis that two independently drawn samples of data originate from the same population, and Murakami (2006) generalized the test statistic for more than two samples. Whereas the expressions of the exact density and distribution functions of the generalized Baumgartner statistic are not yet found, the characteristic function of its limiting distribution has been obtained. Due to the development of computational power, the Fourier series approximation can be readily utilized to accurately and efficiently approximate its density function based on its Laplace transform. Numerical examples show that the Fourier series method provides an accurate approximation for statistical quantities of the generalized Baumgartner statistic.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.199-210
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• 1997

Using regression methods based on quasi-likelihood equation, one only needs to specify the conditional mean and variance functions for the response variable in the analysis. In this paper, an omnibus lack-of-fit test is proposed to test the validity of these two functions. Our test is consistent against the alternative under which either the mean or the variance is not the one specified in the null hypothesis. The large-sample null distribution of our test statistics can be approximated through simulations. Extensive numerical studies are performed to demonstrate that the new test preserves the prescribed type I error probability. Power comparisons are conducted to show the advantage of the new proposal.