• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.933-945
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• 2008

The genetic association test on age of onset trait aims to detect the putative gene by means of linear rank tests for a significant trend of onset distributions with genotypes. However, due to the selective sampling of recruiting subjects with ages less than a pre-specified limit, the genotype groups are subject to substantially different censored distributions and thus this is one reason for the low efficiencies in the linear rank tests. In testing the equality of two survival distributions, log-rank statistic is preferred to the Wilcoxon statistic, when censored observations are nonignorable. Therefore, for more then two groups, we propose a generalized log-rank test for trend as a genetic association test. Monte Carlo studies are conducted to investigate the performances of the test statistics examined in this paper.

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

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.569-580
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• 2015

Log-rank is widely used for testing equality of two survival functions, and this method is efficient only under the proportional hazard assumption. However, crossing survival functions are common in practice. Therefore, many approaches have been suggested to test equality of them. This study considered several methods; Renyi type test, modified Kolmogorov-Smirnov and Cramer-von Mises test, and weighted Log-rank test, which can be applied when the survival functions cross, and simulated power of those methods. Based on the simulation results, we provide the useful information to choose a suitable approach in a given situation.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.115-127
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• 2017

This paper proposes a Bayesian test for the equivalence of survival functions in multiple groups. Proposed Bayesian test use the model of Cox's regression with time-varying coefficients. B-spline expansions are used for the time-varying coefficients, and the proposed test use only the partial likelihood, which provides easier computations. Various simulations of the proposed test and typical tests such as log-rank and Fleming and Harrington tests were conducted. This result shows that the proposed test is consistent as data size increase. Specifically, the power of the proposed test is high despite the existence of crossing hazards. The proposed test is based on a Bayesian approach, which is more flexible when used in multiple tests. The proposed test can therefore perform various tests simultaneously. Real data analysis of Larynx Cancer Data was conducted to assess applicability.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.325-334
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• 2009

In this research, we propose a nonparametric test procedure for the right censored and grouped data under the additive hazards model. For deriving the test statistics, we use the likelihood principle. Then we illustrate proposed test with an example and compare the performance with other procedure by obtaining empirical powers. Finally we discuss some interesting features concerning the proposed test.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.115-121
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• 2017

This paper is to introduce the main modeling assumptions and data structures associated with right-censored data to describe the successful methodological ideas for analyzing such a field-failure-data when components operating in different environments. The Kaplan - Meier method is the most popular method used for survival analysis. Together with the log-rank test, it may provide us with an opportunity to estimate survival probabilities and to compare survival between groups. An important advantage of the Kaplan - Meier curve is that the method can take into account some types of censored data, particularly right-censoring. The above non-parametric method was used to verify the equality of parts life used in different environments. After that, we performed the life distribution analysis using the parametric method. We simulated data from three distributions: exponential, normal, and Weibull. This allowed us to compare the results of the estimates to the known true values and to quantify the reliability indices. Here we used the Akaike information criterion to find a suitable life time distribution. If the Akaike information criterion is the smallest, the best model of failure data is presented. In this paper, no-nparametrics and parametrics methods are analyzed using R program which is a popular statistical program.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.373-384
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• 2003

In this paper, we formulate multivariate one-sided alternatives and propose a class of nonparametric tests for possibly right censored data. We obtain the asymptotic tail probability (or p-value) by showing that our proposed test statistics have asymptotically multivariate normal distributions. Also, we illustrate our procedure with an example and compare it with other procedures in terms of empirical powers for the bivariate case. Finally, we discuss some properties of our test.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5601-5605
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• 2014

Background: Agrocybe aegerita Lectin (AAL) has been identified to have high affinity for sulfated and ${\alpha}2$-3-linked sialic acid glycoconjugates, especially the sulfated and sialyl TF (Thomsen-Friedenreich) disaccharide. This study was conducted to investigate the clinicopathological and prognostic value of AAL in identifying aberrant glycosylation in colorectal cancer (CRC). Materials and Methods: Glycoconjugate expression in 59 CRC tissues were detected using AAL-histochemistry. Clinicopathological associates of expression were analyzed with chisquare test or Fisher's exact test. Relationships between expression and the various clinicopathological parameters was estimated using Kaplan-Meier analysis and Cox regression models. Results: AAL specific glycoconjugate expression was significantly higher in tumor than corresponding normal tissues (66.1% and 46.1%, respectively, p=0.037), correlating with depth of invasion (p=0.015) and TNM stage (p=0.024). Patients with lower expression levels had a significantly higher survival rate than those with higher expression (p=0.046 by log rank test and p=0.047 by Breslow test for overall survival; p=0.054 by log rank test and P=0.038 by Breslow test for progress free survival). A marginally significant association was found between AAL specific glycoconjugate expression and overall survival by univariate Cox regression analysis (p=0.059). Conclusions: Lower AAL specific glycoconjugate expression is a significant favorable prognostic factor for overall and progress free survival in CRC. This is the first report about the employment of AAL for histochemical analysis of cancer tissues. The binding characteristics of AAL means it has potential to become a powerful tool for the glycan investigation and clinical application.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.487-496
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• 2008

Recently survival analysis becomes popular in a variety of fields so that a number of statistical packages are developed for analyzing the survival model. In this paper, several types of survival models are introduced and considered briefly. In addition, widely used three packages(SAS, SPSS, and STATA) for survival data are reviewed and their characteristics are investigated.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.747-756
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• 2010

With the recent recession, studies on the economy are actively being conducted throughout the industry. Based on the Small Business data registered in the Credit Guarantee Fund, we estimated the survival probability in the context of the survival analysis. We also analyzed the survival time for the construction and the other industries which are distinguished depending on the types of business and assets in the Small Business. The survival probability was estimated by using the life-table and the difference between the survival probabilities for the different types of business was described via the method of the Log-rank test and the Wilcoxon test. We found that the small business with over one billion asset has the highest survival probability and that with less than 1000 million asset showed the similar survival probability. In terms of types of business Wholesale and Retail trade industry and Services were relatively high in the survival probability than Light, Heavy, and the construction industries. Especially the construction industry showed the lowest survival probability. Most of the Small Business tend to increase in the hazard rate over time.