• Title/Summary/Keyword: Biostatistics

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Statistical Bias and Inflated Variance in the Genehunter Nonparametric Linkage Test Statistic

  • Song, Hae-Hiang;Choi, Eun-Kyeong
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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    • pp.373-381
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    • 2009
  • Evidence of linkage is expressed as a decreasing trend of the squared trait difference of two siblings with increasing identical by descent scores. In contrast to successes in the application of a parametric approach of Haseman-Elston regression, notably low powers are demonstrated in the nonparametric linkage analysis methods for complex traits and diseases with sib-pairs data. We report that the Genehunter nonparametric linkage statistic is biased and furthermore the variance formula that they used is an inflated one, and this is one reason for a low performance. Thus, we propose bias-corrected nonparametric linkage statistics. Simulation studies comparing our proposed nonparametric test statistics versus the existing test statistics suggest that the bias-corrected new nonparametric test statistics are more powerful and attains efficiencies close to that of Haseman-Elston regression.

Spatial Prediction Based on the Bayesian Kriging with Box-Cox Transformation

  • Choi, Jung-Soon;Park, Man-Sik
    • Communications for Statistical Applications and Methods
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    • v.16 no.5
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    • pp.851-858
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    • 2009
  • In the last decades, there has been much interest in climate variability because its change has dramatic effects on humanity. Especially, the precipitation data are measured over space and their spatial association is so complicated. So we should take into account such a spatial dependency structure while analyzing the data. However, in linear models for analyzing the data, data sets show severely skewed distribution. In the paper, we consider the Box-Cox transformation to satisfy the normal distribution prior to the analysis, and employ a Bayesian hierarchical framework to investigate the spatial patterns. The data set we considered is monthly average precipitation of the third quarter of 2007 obtained from 347 automated monitoring stations in Contiguous South Korea.

Nonparametric method using placement in a randomized complete block design (랜덤화 블록 계획법에서 위치를 이용한 비모수 검정법)

  • Sim, Sujin;Kim, Dongjae
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1401-1408
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    • 2013
  • Kim and Kim (1992) proposed typical nonparametric method for umbrella alternative in randomized block design with replications. In this paper, We consider a test procedure for umbrella alternatives in a randomized block design using extension of the two sample placement tests described in Orban and Wolfe (1982) and treatment tests described in Kim (1999). We perform a Monte Carlo study to compare the empirical powers of the test statistics for underlying distributions.

Nonparametric Tests for 2×2 Cross-Over Design

  • Gee, Kyuhoon;Kim, Dongjae
    • Communications for Statistical Applications and Methods
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    • v.19 no.6
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    • pp.781-791
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    • 2012
  • A $2{\times}2$ Cross-over design is widely used in clinical trials for comparison studies of two kinds of drugs or medical treatments. This design has many statistical methods such as Hills-Armitage's (1979) method or Koch's (1972) method. In this paper, we propose a nonparametric test for $2{\times}2$ Cross-over design based on a two-sample test suggested by Baumgartner et al. (1998). In addition, a Monte Carlo simulation study is adapted to compare the power of the proposed methods with those of previous methods.

Maximum Tolerated Dose Estimate by Curve Fitting in Phase I Clinical Trial (제1상 임상시험에서 곡선적합을 이용한 MTD 추정법)

  • Heo, Eun-Ha;Kim, Dong-Jae
    • Communications for Statistical Applications and Methods
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    • v.18 no.2
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    • pp.179-187
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    • 2011
  • The purpose of a Phase I clinical trial is to estimate the maximum tolerated dose, MTD, of a new drug. In this paper, the MTD estimation method is suggested by curve fitting the dose-toxicity data to an S-shaped curve. The suggested MTD estimation method is compared with established MTD estimation procedures using a Monte Carlo simulation study.

Quantile-based Nonparametric Test for Comparing Two Diagnostic Tests

  • Kim, Young-Min;Song, Hae-Hiang
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.609-621
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    • 2007
  • Diagnostic test results, which are approximately normal with a few number of outliers, but non-normal probability distribution, are frequently observed in practice. In the evaluation of two diagnostic tests, Greenhouse and Mantel (1950) proposed a parametric test under the assumption of normality but this test is inappropriate for the above non-normal case. In this paper, we propose a computationally simple nonparametric test that is based on quantile estimators of mean and standard deviation, instead of the moment-based mean and standard deviation as in some parametric tests. Parametric and nonparametric tests are compared with simulations under the assumption of, respectively, normality and non-normality, and under various combinations of the probability distributions for the normal and diseased groups.

Parallelism Test of Slope in Simple Linear Regression Models (회귀모형의 기울기에 대한 품행성 검정)

  • Park, Hyun-Wook;Kim, Dong-Jae
    • Communications for Statistical Applications and Methods
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    • v.16 no.1
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    • pp.75-83
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    • 2009
  • Parallelism tests are proposed for slope in the simple linear regression models. In this paper, we suggest the parametric test using HSD testing method (Tukey,1953) and distribution-free test using Kruskal-wallis (1952) for more than three slopes. Monte Carlo simulation study is adapted to compare the power of the proposed methods with Wilks' Lambda multivariate procedure.

Performance Analysis of a Parallel System Having a Cold Standby Unit

  • Sharma, S.C.;Bae, S.;Baek, J.B.;Singh, K.P.
    • International Journal of Reliability and Applications
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    • v.8 no.1
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    • pp.67-82
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    • 2007
  • This paper deals with the effectiveness analysis of an engineering system, which has two units of different strengths in parallel and one unit as a cold standby unit. Failure times for all the units have negative exponential distribution whereas their repair times have general distribution. Single server caters the need for the system. The effectiveness analysis of the system is done by using regenerative point technique. The different measures of effectiveness such as mean sojourn time, mean time to system failure, availability, busy period, etc, are derived. Cost factors also taken into consideration.

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CONTINUOUS-TIME MARKOV MODEL FOR GERIATRIC PATIENTS BEHAVIOR. OPTIMIZATION OF T도 BED OCCUPANCY AND COMPUTER SIMULATION

  • Gorunescu, Marina;Gorunescu, Florin;Prodan, Augustin
    • Journal of applied mathematics & informatics
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    • v.9 no.1
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    • pp.185-195
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    • 2002
  • Previous research has shown that the flow of patients around departments of geriatric medicine and ex-patients in the community may be-modelled by the application of a mixed-exponential distribution. In this proper we considered a ave-compartment model using a continuous-time Markov process to describe the flow of patients. Using a M/ph/c queuing model, we present a way of optimizing the number of beds in order to maintain an acceptable delay probability a sufficiently low level. Finally, we constructed a Java computer simulation, using data from St George's Hospital, London.

Nonparametric procedures using placement in randomized block design with replications (반복이 있는 랜덤화 블록 계획법의 위치를 이용한 비모수 검정법)

  • Lee, Sang-Yi;Kim, Dong-Jae
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1105-1112
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    • 2011
  • Mack (1981), Skilling and Wolfe (1977, 1978) proposed typical nonparametric method in randomized block design with replications. In this paper, we proposed the procedures based on placement as extension of the two sample placement tests described in Orban and Wolfe (1982) and treatment versus control tests described in Kim (1999). Also Monte Carlo simulation study is adapted to compare power of the proposed procedure with those of previous procedures.