• Korean Journal of Radiology
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• v.25 no.4
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• pp.325-327
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• 2024

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.175-181
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• 2002

cDNA microarray experiments permit us to investigate the expression levels of thousands of genes simultaneously and to make it easy to compare gene expression from different populations. However, researchers are asked to be cautious in interpreting the results because of the unexpected sources of variation such as systematic errors from the microarrayer and the difference of cDNA dye intensity. And the scanner itself calculates both of mean and median of the signal and background pixels, so it follows a selection which raw data will be used in analysis. In this paper, we compare the results in each case of using mean and median from the raw data and normalization methods in reducing the systematic errors with arm's skin cells of old and young males. Using median is preferable to mean because the distribution of the test statistic (t-statistic) from the median is more close to normal distribution than that from mean. Scaled print tip normalization is better than global or lowess normalization due to the distribution of the test-statistic.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.61-70
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• 2014

A randomized block design is a method to apply a treatment into the experimental unit of each block after dividing into several blocks with a binded homogeneous experimental unit. Jonckheere (1964) and Terpstra (1952), Page (1963), Hollander (1967) proposed various methods of ordered alternative in randomized block design. Especially, Page (1963) test is a weighted combination of within block rank sums for ordered alternatives. In this paper, we suggest a new nonparametric method expanding the Page test for an ordered alternative. A Monte Carlo simulation study is also adapted to compare the power of the proposed methods with previous methods.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.33-45
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• 2012

The primary interest of drug development studies is to estimate the smallest dose that shows a significant difference from the zero-dose control. The smallest dose is called the Minimum Effective dose(MED). In this paper, we suggest a nonparametric procedure to simultaneously find the MED of each group based on placements. The Monte Carlo simulation is adapted to estimate the power and the family-wise error rate(FWE) of the new procedures with those of discussed nonparametric tests to find MED.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1081-1091
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• 2010

Clinical trials are often carried out as multi-center studies because the patients enrolled for a trial study are very limited in one particular hospital. In these circumstances, the use of an ordinary Jonckheere (1954) and Terpstra (1952) test for testing trend among several independent treatment groups is invalid. We propose a the stratified Jonckheere-Terpstra test based on van Elteren (1960)'s stratified test of Wilcoxon (1945) statistics and an application of our method is demonstrated through example data. A simulation study compares the efficiency of stratified and unstratified Jonckheere-Terpstra trend tests.

• Journal of Preventive Medicine and Public Health
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• v.43 no.6
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• pp.459-471
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• 2010

The main behavioural and environmental risk factors for cancer mortality in the world are related to diet and physical inactivity, use of addictive substances, sexual and reproductive health, exposure to air pollution and use of contaminated needles. The population attributable fraction for all cancer sites worldwide considering the joint effect of these factors is about 35% (34 % for low- and middle-income countries and 37% for high-income countries). Seventy-one percent of lung cancer deaths are caused by tobacco use (lung cancer is the leading cause of cancer death globally). The combined effects of tobacco use, low fruit and vegetable intake, urban air pollution, and indoor smoke from household use of solid fuels cause 76% of lung cancer deaths. Exposure to these behavioural and environmental factors is preventable; modifications in lifestyle could have a large impact in reducing the cancer burden worldwide. The evidence of association between lifestyle factors and cancer, as well as the main international recommendations for prevention are briefly reviewed and commented upon here.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3979-3982
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• 2016

Background: Thailand remains a primarily agricultural country and Thai farmers are heavy users of pesticides. Coincidentally the incidence of cholangio carcinoma (CCA) is high in parts of the country, but no previous study has examined any association between the two. Materials and Methods: The present matched, case-control study covered patients admitted to Srinagarind Hospital, Khon Kaen University, Thailand. The case group comprised 210 cases diagnosed with CCA and the control group 840 diagnosed with other diseases. Cases and controls were matched for sex, age within five years, and date of admission within three months. Multiple conditional logistic regression was used for the analysis. Results: After adjusting for potential confounders, pesticide use as compared with never used pesticide was not associated with CCA (ORadj=1.11, 95% CI: 0.77, 1.60) and neither was there any significant relationship between CCA and duration of pesticide use, type or number of types pesticide use. Conclusions: The current study thus found no association between pesticide use and CCA.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1085-1091
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• 2012

Phase I clinical trials are designed to identify an appropriate dose; the maximum tolerated dose, which assures safety of a new drug by evaluating the toxicity at each dose-level. The adjusted maximum tolerated dose estimation is presented by stopping rule in phase I clinical trial on this research. The suggested maximum tolerated dose estimation is compared to the standard method3 and NM method using a Monte Carlo simulation study.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1193-1196
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• 2016

Background: Colorectal cancer (CRC) is the commonest malignancy in the lower gastrointestinal tract in both men and women. It is the third leading cause of cancer-dependent death in the world. In Iran the incidence of colorectal cancer has increased during the last 25 years. Materials and Methods: In this article we analyzed the survival of 447 colorectal patients of Taleghani hospital in Tehran using parametric competing-risks models. The cancers of these patients were diagnosed during 1985 - 2012 and followed up to 2013. The purpose was to assess the association between survival of patients with colorectal cancer in the presence of competing-risks and prognostic factors using parametric models. The analysis was carried out using R software version 3.0.2. Results: The prognostic variables included in the model were age at diagnosis, tumour site, body mass index and sex. The effect of age at diagnosis and body mass index on survival time was statistically significant. The median survival for Iranian patients with colorectal cancer is about 20 years. Conclusions: Survival function based on Weibull model compared with Kaplan-Meier survival function is smooth. Iranian data suggest a younger age distribution compared to Western reports for CRC.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1533-1537
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• 2012

In general, breast cancer is the most common malignancy among women in developed as well as some developing countries, often being the second leading cause of cancer mortality after lung cancer. Using a parametric log-logistic model to consider the effects of prognostic factors, the present study focused on the 5-year survival of women with the diagnosis of breast cancer in Southern Iran. A total of 1,148 women who were diagnosed with primary invasive breast cancer from January 2001 to January 2005 were included and divided into three prognosis groups: poor, medium, and good. The survival times as well as the hazard rates of the three different groups were compared. The log-logistic model was employed as the best parametric model which could explain survival times. The hazard rates of the poor and the medium prognosis groups were respectively 13 and 3 times greater than in the good prognosis group. Also, the difference between the overall survival rates of the poor and the medium prognosis groups was highly significant in comparison to the good prognosis group. Use of the parametric log-logistic model - also a proportional odds model - allowed assessment of the natural process of the disease based on hazard and identification of trends.