• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.705-713
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• 2010

Predicting survival from microarray data is not easy due to the problem of high dimensionality of data and the existence of censored observations. Also the limitation of individual gene analysis causes the shift of focus to the level of gene sets with functionally related genes. For developing a survival prediction model based on pathway information, the methods for selecting a supergene using principal component analysis and testing its significance for each pathway are discussed. Besides, the performance of gene filtering is compared.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4281-4284
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• 2012

Background: Osteosarcoma is the most common bone cancer in children, responsible for a high rate of amputation and death. This is the first long-term, population-based, epidemiologic and survival study in Thailand. Objective: To study the incidence and survival rates of pediatric osteosarcoma in Khon Kaen. Method: Childhood osteosarcoma cases (0-19 years) diagnosed between 1985-2010 were reviewed. The data were retrieved from the population-based data set of the Khon Kaen Cancer Registry and medical records from Srinagarind Hospital, Faculty of Medicine, Khon Kaen University. All cases were censored until the end of April 2012. The age-standardized incidence rate (ASR) was calculated using the standard method. Survival experience was analyzed using the standard survival function (STATA 9.0) and presented with a Kaplan-Meier curve. Results: 58 cases were enrolled. The overall ASR was 14.1 per million. Males and females were equally affected. The peak incidence was for 15-19 year-olds in both sexes (ASR=10.4 per million in males and 8.5 in females). The 5-year overall survival rate was 27.6% (95% CI: 15.8-40.8%). The median survival time was 1.6 years (95% CI: 1.2-2.1). In a subgroup analysis, the patients who received only chemotherapy survived longer (5-year survival 45.7%, median survival time 4.1 years, p=0.12). Conclusion: The incidence rate for childhood osteosarcoma was slightly less than those reported for Western countries. The survival rate was also lower than reports from developed countries. Further evaluation of the treatment protocol and risk factor stratification is needed.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.325-337
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• 2017

In this paper, we proposed a new long-term lifetime distribution with four parameters inserted in a risk competitive scenario with decreasing, increasing and unimodal hazard rate functions, namely the Weibull-Poisson long-term distribution. This new distribution arises from a scenario of competitive latent risk, in which the lifetime associated to the particular risk is not observable, and where only the minimum lifetime value among all risks is noticed in a long-term context. However, it can also be used in any other situation as long as it fits the data well. The Weibull-Poisson long-term distribution is presented as a particular case for the new exponential-Poisson long-term distribution and Weibull long-term distribution. The properties of the proposed distribution were discussed, including its probability density, survival and hazard functions and explicit algebraic formulas for its order statistics. Assuming censored data, we considered the maximum likelihood approach for parameter estimation. For different parameter settings, sample sizes, and censoring percentages various simulation studies were performed to study the mean square error of the maximum likelihood estimative, and compare the performance of the model proposed with the particular cases. The selection criteria Akaike information criterion, Bayesian information criterion, and likelihood ratio test were used for the model selection. The relevance of the approach was illustrated on two real datasets of where the new model was compared with its particular cases observing its potential and competitiveness.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.533-542
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• 2002

In this paper, a covariate adjusted logrank test is considered for censored paired data under the Cox proportional hazard model. The proposed score test resembles the adjusted logrank test of Tsiatis, Rosner and Tritchler (1985), which is derived from the partial likelihood. The dependence structure for paired data is accommodated into the test statistic by using' sum of square type' variance estimators. Several weight functions are also considered, which produce a class of covariate adjusted weighted logrank tests. Asymptotic normality of the proposed test is established and simulation studies with moderate sample size show the proposed test works well, particularly when there are dependence structure between treatment and covariates.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.425-445
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• 2021

A generalization of the log-logistic (LL) distribution called exponentiated log-logistic (ELL) distribution on lines of exponentiated Weibull distribution is considered. In this paper, based on progressive type-II censored samples, we have derived the maximum likelihood estimators and Bayes estimators for three parameters, the survival function and hazard function of the ELL distribution. Then, under the balanced squared error loss (BSEL) and the balanced linex loss (BLEL) functions, their corresponding Bayes estimators are obtained using Lindley's approximation (see Jung and Chung, 2018; Lindley, 1980), Tierney-Kadane approximation (see Tierney and Kadane, 1986) and Markov Chain Monte Carlo methods (see Hastings, 1970; Gelfand and Smith, 1990). Here, to check the convergence of MCMC chains, the Gelman and Rubin diagnostic (see Gelman and Rubin, 1992; Brooks and Gelman, 1997) was used. On the basis of their risks, the performances of their Bayes estimators are compared with maximum likelihood estimators in the simulation studies. In this paper, research supports the conclusion that ELL distribution is an efficient distribution to modeling data in the analysis of survival data. On top of that, Bayes estimators under various loss functions are useful for many estimation problems.

• Genomics & Informatics
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• v.21 no.3
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• pp.28.1-28.13
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• 2023

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.1729-1732
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• 2016

In the patients with metastatic colorectal cancer (mCRC), RAS testing is the first step to identify those that could benefit from anti-EGFR therapy. This study examined associations between KRAS mutations and clinicopathological and survival data in Iranian patients with mCRC. Between 2008 to2015 in a retrospective study, 83 cases of mCRC were referred to the Clinic of Medical Oncology. The mean follow-up was 45 months that there were 27 deaths. The 3 patients that did not complete follow-up were censored from the study. KRAS and NRAS were analyzed using allele-specific PCR primers and pyrosequencing in exons 2, 3 and 4. Multivariate survival analysis using Cox's regression model was used for affecting of variables on overall survival (OS). The mean age at diagnosis for patients was 57.7 (range, 18 to 80 years) and 61.4% were male. There was no significant different between prognostic factors and KRAS mutation with wild-type. Also, There was no significant different between KRAS mutation and KRAS wild-type for survival, but there was a significant different between KRAS 12 and 13 mutations for survival (HR 0.13, 95% CI 0.03-0.66, P=0.01). In conclusion, the prevalence of KRAS mutations in CRC patients was below 50% but higher than in other studies in Iran. As in many studies, patients with KRAS 12 mutations had better OS thn those with KRAS 13 mutation. In addition to KRAS testing, other biomarkers are needed to determine the best treatment for patients with mCRC.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.3
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• pp.90-103
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• 1998

The purposes of this study are to estimate the economic value and reasonable entrance fee of the Yeido Park, which is under construction in Seoul, by conduct the face-to-face interview. A total of 645 daults were selected by two stage cluster sampling. The senario was designed to meet the requirements for doubgle-bounded dichotomous choice CVM, and distributed with the photograph to epict and compare the current and suggested conditions. A donation vehicle and entrance fee were utilized to find the possibility of strategic behaviors and protest zero, and to make the data estimatable tfor interval censored survival analysis. Date was calibrated by the survival analysis to eleminate the 'fat-tail problem'. Weibull distribution was assumed as a baseline distrubution. The mean WTP of donation and entrance fee was ￦5,281 and ￦783, respectively. The economic value of this park was determined by aggregating the mean value, giving a total WTP for the population of ￦36,861,645,000. This economic value was composed with the use value and existence value. The calibrationi of the Weibull proportional hazard model showed that nearness to the park, age, intention to isit the park, and educational attainment were significant independent variable to influence an amount of donation.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.311-319
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• 2012

The simplest and the most important distribution in survival analysis is exponential distribution. Koziol and Green (1976) derived Cram$\acute{e}$r-von Mises statistic's randomly censored version based on the Kaplan-Meier product limit estimate of the distribution function; however, it could not be practical for a real data set since the statistic is for testing a simple goodness of fit hypothesis. We generalized it to the composite hypothesis for exponentiality with an unknown scale parameter. We also considered the classical Kolmogorov-Smirnov statistic and generalized it by the exact same way. The two statistics are compared through a simulation study. As a result, we can see that the generalized Koziol-Green statistic has better power in most of the alternative distributions considered.

• Journal of Korean Society for Quality Management
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• v.23 no.1
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• pp.15-28
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• 1995

We consider a step-stress life testing which is devised for a two-component parallel system with considerably long life time. To describe such a system, we use an exponential distribution as the survival function. The lift distribution is assumed between the log mean life time and the stress with the cumulative exposure model. The criterion for optimality is to minimize the sum of the variances of the maximum likelihood estimators of the mean life times of each part under the normal stress.