• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.797-806
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• 2013

Meta-analysis is used in variety of areas to synthesize the results of previous studies. Among the methods for Meta-analysis, combining p-values is the simplest method; in addition Tippett (1931), Fisher (1932), Stuoffer at al. (1949), proposed various methods to combine p-values. We propose a new method to combine p-values based on exponential distribution. A Monte Carlo simulation study compares the power of the proposed methods with previous methods.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.13-20
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• 2014

Phase I Clinical Trials estimate a Maximum Tolerated Dose(MTD). In this paper, an MTD estimation method applied stopping rule is proposed for Phase I Clinical Trials. The suggested MTD estimation method is compared to the Continual Reassessment Method(CRM) method using a Monte Carlo simulation study.

• 대한예방의학회:학술대회논문집
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• 2001.10a
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• pp.325-326
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• 2001

• 대한예방의학회:학술대회논문집
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• 2005.10a
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• pp.402-402
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• 2005

• 대한예방의학회:학술대회논문집
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• 2005.10a
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• pp.297-297
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• 2005

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.77-84
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• 2012

Mack and Skillings (1980) proposed a typical nonparametric method in a randomized block design with replications. However, this method may lose information because of the use of average observations instead of individual observations. In this paper, we proposed a nonparametric method that employed an aligned method suggested by Hodges and Lehmann (1962) under a randomized block design with replications. In addition, the comparative results of a Monte Carlo power study are presented.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.57-64
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• 2012

Phase I clinical trials determine the maximum tolerated dose(MTD) of a new drug. In this paper, we proposed a two-stage MTD estimation method by a Stopping rule in a phase I clinical trial. The suggested MTD estimation method is compared to the standard design(SM3) and the continual reassessment method(CRM) using a Monte Carlo simulation study.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.635-649
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• 2006

In this paper, we perform a simulation study of genetic model-free age-of-onset methods in linkage tests which has been proposed by Zhu et al. (1997). They performe. Haseman-Elston regression on a set of bipolar pedigree data using each of three dependent variables: a binary trait indicating disease concordance or discordance, a binary trait adjusted for age-of-onset, and the residuals from a survival analysis. We compare the powers of the proposed test statistics for various situations. Simulations that we have carried out show that the gains in power are observed when the residuals from a survival analysis are used in linkage tests.

• 대한예방의학회:학술대회논문집
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• 2002.10a
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• pp.431-431
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• 2002

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.721-729
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• 2012

Various methods control the influence of a covariate on a response variable. These methods are analysis of covariance(ANCOVA), RANK ANCOVA, ANOVA of (covariate-adjusted) residuals, and Kruskal-Wallis tests on residuals. Covariate-adjusted residuals are obtained from the overall regression line fit to the entire data set that ignore the treatment levels or factors. It is demonstrated that the methods on covariate-adjusted residuals are only appropriate when the regression lines are parallel and covariate means are equal for all treatments. In this paper, we proposed the new nonparametric method on the ANCOVA model, as applying joint placement in a one-way layout on residuals as described in Chung and Kim (2007). A Monte Carlo simulation study is adapted to compare the power of the proposed procedure with those of the previous procedure.