• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1169-1182
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• 2016

Cancer is a typical cause of death in Korea that becomes a major issue in health care. According to Cause of Death Statistics (2014) by National Statistical Office, SMRs (standardized mortality rates) in Busan were counted as the highest among all cities. In this paper, we used data of Busan Regional Cancer Center to estimate the extent of the cancer incidence rate and cancer mortality rate. The data are considered in small areas of administrative units such as Gu/Dong from years 2003 to 2009. All cancer including four major cancers (stomach cancer, colorectal cancer, lung cancer, liver cancer) have been analyzed. We carried out model selection and parameter estimation using spatial multi-level model incorporating a spatial correlation. For the spatial effects, CAR (conditional autoregressive model) has been assumed.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.57-69
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• 2011

Researchers are continuously trying to find innovative diagnostic tests and published articles are accumulating at an enormous rate in many medical fields. Meta-analysis enables previously published study results to be reviewed and summarized; therefore, an objective assessment of diagnostic tests can be done with a meta-analysis of sensitivities and specificities. Data obtained by applying two diagnostic tests to a well-defined group of diseased patients produce a pair of sensitivity and by applying the same medical tests to a group of non-diseased subjects produce a pair of specificity. The statistical tests in the meta-analysis need to consider the correlatedness of the results from two diagnostic tests applied to the same diseased and non-diseased subjects. The associations between two diagnostic test results are often found to be unequal for the diseased and non-diseased subjects. In this paper, multivariate meta-analytic methods are studied by taking into account the different associations between correlated variables. On the basis of Monte Carlo simulations, we evaluate the performance of the multivariate meta-analysis methods proposed in this paper.

• Korean Journal of Environmental Biology
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• v.35 no.4
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• pp.640-647
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• 2017

The need for an efficient sampling technique to collect aquatic organisms has risen with the increase of interest in rice paddy fields, which have been recognized as important ecosystems supporting biodiversity. In the present study, a submerged funnel trap used with the assistance of attracting agents (fish meal and chemical light) was designed as an easy, objective and quantitative tool for collecting aquatic organisms in the rice paddy fields. The preference for collecting aquatic organisms as a means for attracting agents was analyzed using a generalized linear mixed model. Also, based on the data of previous research, we compared the community composition of the aquatic macroinvertebrates, which were collected using the quadrat method, and newly designed submerged funnel traps, by analyzing non-metric multidimensional scaling. The results showed that the catching efficiency of 18 of the total 65 taxa was affected by the attracting agents. 12 taxa including Pomacea canaliculata, Hippeutis cantori, Austropeplea ollula, Erpobdella lineata, Ostracoda spp. Branchinella kugenumaensis, Hydaticus grammicus, Rhantus pulverosus, Chironomidae spp., Rana nigromaculata, Cobitidae spp. etc., favored fish meal and 6 taxa including Ischnura asiatica, Coenagrionidae spp. Sternolophus rufipes etc., were attracted by chemical light. The submerged funnel trap used as a measurement tool for biodiversity was less applicable than the quadrat method; however, it was more effective for the selective collection of specific taxa. We expect that this newly designed trap can be a simple and quantitative method for collecting aquatic organisms, and could be used for long term and extensive surveys in rice paddy fields in the future.