• The Korean Journal of Applied Statistics
• /
• v.7 no.2
• /
• pp.79-88
• /
• 1994

Weighted log rank test is a widely applicable test when one is interested in detecting the differences between two groups. In man clinical trials it is common to see no differences in early experiments and does show significant differences later. We propose new weighted log rank test and illustrate it through an example. We also examine the empirical powers and show that the proposed test is more sensitive to detect late differences.

• Communications for Statistical Applications and Methods
• /
• v.25 no.1
• /
• pp.71-78
• /
• 2018

In this study, we consider the likelihood ratio test for the covariance matrix of the multivariate normal data. For this, we propose a method for obtaining null distributions of the likelihood ratio statistics by the Monte-Carlo approach when it is difficult to derive the exact null distributions theoretically. Then we compare the performance and precision of distributions obtained by the asymptotic normality and the Monte-Carlo method for the likelihood ratio test through a simulation study. Finally we discuss some interesting features related to the likelihood ratio test for the covariance matrix and the Monte-Carlo method for obtaining null distributions for the likelihood ratio statistics.

• Journal of Korean Society for Quality Management
• /
• v.15 no.2
• /
• pp.50-54
• /
• 1987

A distribution-free rank test for parallelism of regression lines against ordered alternatives is considered. The proposed test statistic is based on the Kepner-Robinson's transformation. The null distribution of the proposed statistic is the same as that of the Wilcoxon signed rank statistic. But, the proposed procedure can be applied only to four or fewer regression lines. The results of a small-sample Monte Carlo study show that the proposed test is comparable with the parametric test in heavy tailed distributions.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
• /
• v.32 no.4
• /
• pp.41-61
• /
• 2019

Background : The current medical statistics used in clinical research are the results of Fisher's significance test and the Neyman-Pearson hypothesis test, which were combined by psychologists. Also, in the philosophical background, it is related to Popper's falsificationism based hypothesis-deductive method and reduction to absurdity. Objectives : This study was designed to find complementary and alternative methods of null hypothesis and alternative hypothesis used for the clinical research methodology of Korean medicine otolaryngology. Methods : The body of this paper was divided into seven part. These are historical background, hypothesis test, hypothesis test method used in the design of clinical study, falsificationism and reduction to absurdity, problem and alternative method of the Neyman-Pearson hypothesis test, diagnosis example of sinusitis differentiation syndromes by Bayesian statistics. Through this process, we found out problems of frequentist statistics and suggested alternative methods. Result & Conclusion : As a solution to the problems of the null hypothesis and the alternative hypothesis, there are effects size, confidence interval, Bayesian statistics and Lakatos methodology of scientific research programmes.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 1998.11a
• /
• pp.259-268
• /
• 1998

A family of test statistics is proposed for testing whether or not the mean residual life(MRL) changes its trend. We do not assume that the turning point or the proportion before the turning point is known. This family includes the test statistic proposed by Aly (1990) and Hawkins, Kochar and Leader (1992) for complete samples. We establish the asymptotic null distribution of test statistics and obtain asymptotic critical values of the asymptotic null distribution using Durbin's approximation. We study Monte Carlo simulation to compare the proposed tests with previously known tests.

• Journal of the Korean Data and Information Science Society
• /
• v.7 no.1
• /
• pp.37-46
• /
• 1996

In this paper, we introduce the goodness of fit test procedure for lifetime distribution using step stress accelerated lifetime data. Using the nonpapametric estimate of acceleration factor, we prove the strong consistence of empirical distribution function under null hypothesis. The critical vailues of Kolmogorov-Smirnov, Anderson-Darling, Cramer-von Mises statistics are computed when the lifetime distibution is assumed to be exponential and Weibull. The power of test statistics are compared through Monte-Cairo simulation study.

• Journal of the Korean Data and Information Science Society
• /
• v.9 no.2
• /
• pp.275-287
• /
• 1998

The goal of this paper is to suggest the goodness-of-fit test statistic for the no effect model. The comparisons of powers on test statistics are conducted with three types alternative modles.

• The Korean Journal of Applied Statistics
• /
• v.7 no.1
• /
• pp.19-34
• /
• 1994

In this paper we propose nonparametric tests of parallelism against umbrella alternatives of slopes in k-regression lines and investigate the asymptotic properties of the proposed test statistics. For the known peak and unknown peak, we suggest the test statistics and show that, from Monte Carlo study, the proposed test statistics have good empirical powers for heavy tailed distributions than the likelihood ratio tests.

• International Journal of Reliability and Applications
• /
• v.6 no.1
• /
• pp.53-64
• /
• 2005

In this paper, we propose a nonparametric test procedure for the multivariate, grouped and right censored data for two sample problem. For the construction of the test statistic, we use the linear rank statistics for each component and apply the permutation principle for obtaining the null distribution. For the large sample case, the asymptotic distribution is derived under the null hypothesis with the additional assumption that two censoring distributions are also equal. Finally, we illustrate our procedure with an example and discuss some concluding remarks. In appendices, we derive the expression of the covariance matrix and prove the asymptotic distribution.

• Journal of Korean Society for Quality Management
• /
• v.34 no.1
• /
• pp.73-77
• /
• 2006

In this paper, the Bayesian procedure for the multiple test of fraction nonconforming, p, is proposed. It is the procedure for checking whether the process is out of control, in control, or under the permissible level for p. The procedure is as follows: first, setting up three types of models, $M_1:p=p_0,\;M_2:pp_0$, second, computing the posterior probability of each model. and then choosing the model with the largest posterior probability as a model most fitted for the observed sample among three competitive models. Finally, the simulation study is performed to examine the proposed method.