• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1243-1251
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• 2010

For clinical trials, it is common to compare the placebo and new drug. The method of calculating a sample size for two independent populations are the t-test that is used for parametric methods, and the Wilcoxon rank-sum test that is used in the non-parametric methods. In this paper, we propose a method that is using Kim's (1994) statistic power based on the linear placement statistic, which was proposed by Orban and Wolfe (1982). We also compare the sample size for the proposed method with that for using Wang et al. (2003)'s sample size formula which is based on Wilcoxon rank-sum test, and with that of t-test for parametric methods.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.151-162
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• 2003

In this paper, we propose two selection procedures for selecting populations better than a control population. The bestness is defined in terms of location parameter. One of the procedures is based on two-sample linear rank statistics whereas the other one is based on a comparatively simple statistic, and is useful when testing time is expensive so that an early termination of an experiment is desirable. The proposed selection procedures are seen to be strongly monotone. Performance of the proposed procedures is assessed through simulation study.

• Journal of the Korean Statistical Society
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• v.18 no.1
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• pp.46-61
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• 1989

This paper is concerned with the development of a nonparametric procedure for the statistical inference about the nonlinear regression parameters. A confidence region and a hypothesis testing procedure based on a class of signed linear rank statistics are proposed and the asymptotic distributions of the test statistic both under the null hypothesis and under a sequence of local alternatives are investigated. Some desirable asymptotic properties including the asymptotic relative efficiency are discussed for various score functions.

• Journal of radiological science and technology
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• v.34 no.3
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• pp.239-244
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• 2011

In this study, we evaluated diffusion weighted imaging (DWI) to investigate whether the DWI parameters can predict characteristic parameters on pathologic specimens of tumor or not. CFPAC-1 was injected subcutaneously on the back flank of athymic nude mice (n=13) then two tumors were initiated on each mouse (2${\times}$13=26 tumors). The mice were sacrificed to make specimen immediately after initial MR imaging then were compared with the MR image. A dedicated high-field (7T) small-animal MR scanner was used for image acquisitions. A T1 and T2 weighted axial image using RARE technique was acquired to measure the T2 values and tumor size. DWI MR was performed for calculating ADC values. To evaluate tumor cellularity and determine the levels of MVD, tumor cells were excised and processed for H-E staining and immunostaining using CD31. T2 values and ADC values were computed and analyzed for each half of the tumors and compared to the correlated specimens slide. Median ADC within each half of mass was compared to the cellularity and MVD in the correlated area of pathologic slide. The mean of ADC value is $0.7327{\times}10^{-3}$ $mm^2/s$ and standard deviation is $0.1075{\times}10^{-3}$ $mm^2/s$. There is a linear relationship between ADC value and tumor necrosis (R2=0.697, p< 0.001). DW image parameters including the ADC values can be utilized as surrogate markers to assess intratumoral neoangiogenesis and change of the internal structure of tumor cells.