• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1045-1054
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• 2011

During clinical trials a researcher is frequently able to observe a disease symptom in a subject as well as a severity score for those who experienced a symptom after a fixed length of treatment. The traditional method to evaluate a decreasing trend in proportion, when there is an intrinsic order in the treatment groups (for example control and two or more treatment groups) is a Cochran-Armitage test, while the method to evaluate a decreasing trend in continuous non-normal data is a Jonckheere-Tersptra test. The Cochran-Armitage test emphasizes the dichotomous data of symptom occurrence and the Jonckheere-Tersptra test emphasizes the continuous non-normal data of severity symptom scores. In this paper we propose new test statistics that consider the combined evidence from a symptom occurrence and disease severity score. We illustrate these methods with example data of schizophrenic inpatients that demonstrated antipsychotic-drug induced constipation. A small-scale simulation is conducted to compare the new trend tests with other trend tests.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.793-804
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• 2009

The hypotheses of difference, ratio and odds ratio between two proportions are used for the non-inferiority trial. The approximate unconditional test suggested by Kang and Chen (2000) based on difference and ratio have the potential problem against the failure rate. When the sample size is small, the type I errors of the asymptotic test using the normal approximation suggested by Chen et al. (2000) tends to exceed the nominal level. Therefore, we propose the approximate unconditional test based on odds ratio and compare the test with the asymptotic test. And we compare the three hypotheses used in the approximate unconditional tests of two proportions with respect to the type I errors and power.

• Korean Journal Plant Pathology
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• v.1 no.2
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• pp.115-121
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• 1985

To improve methods of screening rice cultivars with field resistance to bacterial leaf blight, testing plant inoculation and neighbor plant inoculation were compared by using 33 rice cultivars. In the testing plant inoculation method, field resistance was evaluated by measuring the leaf areas diseased on the new leaves expanded after the inoculation. Varietal differences in field resistance were recognized more clearly by the testing plant inoculation method than by the neighbor plant inoculation method. Highly significant correlation was observed between the results of the two methods. Some rice cultivars such as, Seomjin, Hangangchal, Taebaeg, Samgang, Milyang 42, Asominori, Java 14, Chugoku 45 and 70X-46 showed remarkable field resistance to bacterial leaf blight. The testing plant inoculation method appeared desirable for screening rice cultivars for the qualitative and field resistance to bacterial leaf blight because of using less labor and less field area than neighbor plant inoculation.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.383-391
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• 2011

This paper presents a modified entropy-based test of fit for the inverse Gaussian distribution. The test is based on the entropy difference of the unknown data-generating distribution and the inverse Gaussian distribution. The entropy difference estimator used as the test statistic is obtained by employing Vasicek's sample entropy as an entropy estimator for the data-generating distribution and the uniformly minimum variance unbiased estimator as an entropy estimator for the inverse Gaussian distribution. The critical values of the test statistic empirically determined are provided in a tabular form. Monte Carlo simulations are performed to compare the proposed test with the previous entropy-based test in terms of power.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.111-120
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• 2006

In a two-stage two-level balanced nested design, type I error rates for the parametric tests and the rank transformed tests for the main effects and the nested effects are in overall similar to each other. Furthermore, powers for the rank transformed statistic for the main effects and the nested effects in a two-stage two-level balanced nested design are generally superior to powers for the parametric statistic When the effect size and the sample size are increased, we can find that powers increase for the parametric statistic and the rank transformed statistic are dramatically improved. Especially for the case of the fixed effects in the asymmetric distributions such as an exponential distribution, powers for the rank transformed tests are quite high rather than powers for the parametric tests.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.127-140
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• 2010

In interim analysis, group sequential tests are widely used for the ethical, scientific, and economic reasons. In this paper, we propose the group sequential tests using both type I and type II error spending rate functions when the response variable is discrete, especially binomial distribution, in the interim analysis. In addition, we propose new error spending rate function which covers the formerly proposed. Our method has good property that is flexible, fast and easily applicable. A numerical simulations are carried out to evaluate our method and it shows good performance.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.241-251
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• 2018

The analysis of gene sets in microarray has advantages in interpreting biological functions and increasing statistical powers. Many statistical methods have been proposed for detecting significant gene sets that show relations between genes and phenotypes, but there is no consensus about which is the best to perform gene sets analysis and permutation based tests are considered as standard tools. When many gene sets are tested simultaneously, a large number of random permutations are needed for multiple testing with a high computational cost. In this paper, several parametric approximations are considered as alternatives of the permutation distribution and the moment based gene set test has shown the best performance for providing p-values of the permutation test closely and quickly on a general framework.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.307-315
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• 2014

An exact distribution of the test statistic to test for multiple outlier candidates does not generally exist; therefore, tests of individual outliers (or tests using simulated critical-values) are usually conducted instead of testing for groups of outliers. This article is on procedures to test outlying observations. We suggest a method that can be applied to arbitrary observations or multiple outlier candidates detected by an outlier detecting method. A Monte Carlo study performance is used to compare the proposed method with others.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.23 no.2
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• pp.118-125
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• 1978

To find out highly resistant gene source to black rot fungus in sweetpotato varieties, a screening test was carried out with inoculated tubers and sprouts in 1976 and 1977. Fifteen varieties out of 165 and 54 varieties out of 161 were highly resistant to black rot in the tuber and sprout tests. respectively. The sprout test showed bigger variation from year to year compared to tuber test. Varieties highly resistant to black rot in both tuber and sprout tests were Suweon # 59, #81, #90, Norin #17, #23. Chilship-il cho, Sachun Jong #36, Hamkao, and Kandee.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.141-146
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• 2000

Shapiro와 Wilk(1972)는 위치모수와 척도모수가 미지인 경우 지수분포의 검정통계량을 제안하였다. 그것은 척도모수의 일반화 최소제곱추정량과 표본분산의 비로 구성되었다. 그러나 이 검정통계량은 일치성을 갖지 않는다. 본 논문에서는 척도모수의 두개의 점근유효추정량으로 구성된 통계량을 고려하고 이의 극한분포를 구하였다. 또한 두 개의 통계량의 검정력을 비교한 결과 제안된 통계량이 변동계수가 1보다 크거나 같은 분포에서 더 좋은 검정력을 가짐을 볼 수 있었다.