• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.673-677
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• 2013

Introduction: Capture-recapture methods have been suggested for reducing costs of disease registration as well as reducing bias in incidence estimations. This study aimed to estimate the gastric cancer incidence in the Tehran metropolis population during 2002-2006. Materials and Methods: We investigated new cases of gastric cancer reported by three sources; death certificates, pathology reports, and medical records to Tehran population-based cancer registry during 2002-2006. $G^2$ statistics and the two-source capture-recapture method were used to select the best-fitted log-linear model and to estimate incidence, respectively. EXCEL software version 2007 and SPSS software version 16 were used for this research. Results: The number of reported cases was 4,463, with an average age of 68.5 (${\pm}12.9$) years. We found the model that combined two sources of data including pathology reports and medical records and furthermore complemented by death certificates as the best model. The reported and the estimated incidences were 11.0 and 27.1 per 100,000 respectively. Conclusions: The incidence estimated by two-source capture-recapture method is about three times higher than the incidence reported by the sources under investigation. It is recommended to move towards the implementation of population-based cancer registration using various sources of data collection to achieve more accurate data.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.891-908
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• 2010

In Korea, the small area estimation method is currently unpopular in generating o cial statistics. Because it may be difficult to determine the reliability for small area estimation, although small area estimation ha a sufficiently good advantage to generate small area statistics for Korea. This paper inspects the method of making small area unemployment through the small area estimation method. To estimate small area unemployment we used an EBLUP-type estimator based on a logistic linear mixed model. To evaluate the EBLUP-type estimator we accomplished the real data analysis and simulation experiment from the population and housing census data. In addition, small area estimates are compared to large sample survey estimates. We found the provided method in this paper is highly recommendable to generate small area unemployment as the official statistics.

• Korean Journal of Community Nutrition
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• v.11 no.6
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• pp.808-813
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• 2006

Until now, South Korea does not have either fortification or enrichment program as intervention tools although the addition of micronutrients to foods is for the most part not regulated. The aim of this study was to determine which scenario would most effectively reduce the proportion of the population with low iron intake while not putting other population groups at risk of excessive intakes. In order to investigate potential dietary consequences of iron fortification we analyzed 2 day dietary record data (n=3,955) from the 2001 National Nutrition Surveys. The Proportion of the population consuming dietary iron less than the estimated average requirement (EAR) ranged from $12.4{\sim}87.5%$ depending upon gender and age group. Iron fortification at the level of 100% of Recommended Intake (RI) per 100g to breads and instant o. dried noodles was estimated to result in a 15% decrease of proportion of those with iron less than EAR, while putting 1.4 % of the population greater than the Upper Limit (UL). Iron fortification appeared to be the most effective for the $15{\sim}19$ year old age group, showing 39% reduction of iron intake insufficiency. The results suggest that carefully designed fortification or enrichment to staple foods may contribute to increase dietary iron intakes of Koreans, especially for the young population with a high prevalence of iron inadequacy. As the estimation in this study was based solely upon dietary intake data, iron intake from supplements should be considered in further studies.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1263-1272
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• 2014

Longitudinal categorical data commonly occur from medical, health, and social sciences. In these data, the correlation of repeated outcomes is taken into account to explain the effects of covariates exactly. In this paper, we introduce marginalized random effects models that are used for the estimation of the population-averaged effects of covariates. We also review how these models have been developed. Real data analysis is presented using the marginalized random effects.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.69-74
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• 2003

The estimation of pest density is a prime concern of Integrated Pest Management (IPM) because the success of artificial intervention such as spraying pestcides or natural enemies depends on pest density. Also, the spatial pattern of pest population within plants or plots has been studies in various ways. In this study, we applied generalized linear mixed model to Tetranychus urticae Koch , two-spotted spider mite count in glasshouse grown roses. For this analysis, the subject-specific as well as pupulation-averaged approaches are used.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.229-244
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• 2007

Among the small area estimation methods, it has been known that hierarchical Bayesian(HB) approach is the most reasonable and effective method. However any model based approaches need good explanatory variables and finding them is the key role in the model based approach. As the lacking of explanatory variables, adopting the spatial terms in the model was introduced. Here in this paper, we evaluate the model based methods with/without spatial terms using the diagnostic methods which were introduced by Brown et al. (2001). And Economic Active Population Survey(2005) is used for data analysis.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.12-19
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• 2011

Drawing on its extensive experience with natural disasters, Japan has been dispatching Japan Disaster Relief (JDR) team to disaster-stricken countries to provide specialist assistance in rescue and medical operations. The JDR team has assisted in the wake of disasters including the 2004 Indian Ocean Earthquake and the 2008 Sichuan Earthquake in China. Information about the affected area is essential for a rapid disaster response. However, it can be difficult to gather information on damages in the immediate post-disaster period. To help overcome this problem, we have built on an Earthquake Damage Estimation System. This system makes it possible to produce distributions of the earthquake's seismic intensity and structural damage based on pre-calculated data such as landform and site amplification factors for Peak Ground Velocity, which are estimated from a Digital Elevation Model, as well as population distribution. The estimation result can be shared with the JDR team and with other international organizations through communications satellite or the Internet, enabling more effective rapid relief operations.

• Korea journal of population studies
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• v.29 no.2
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• pp.53-88
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• 2006

The major aim of this paper is to develop a hypothetical set of age-specific fertility rates which are logically derived and reasonably accurate in the projection of future population. The first procedure is to select a generalized log-gamma distribution model, which includes Coale-McNeil nuptiality model, in order to estimate and project a set of age-specific fertility rates by birth cohort and birth order. The second is to apply the log-gamma model with an empirical adjustment to the actual data to estimate and project the future fertility rates for relatively young birth cohorts who did not complete their reproductive career. This study reconstructs or translates a set of cohort age-specific fertility rates into a set of period age-specific fertility rates which must be hypothesized in order to establish the broader framework of future population projection. For example, the fertility at age 20 in the year of 2020 is the fertility at age 20 for the cohort born in 1990, while the fertility at age 21 in the year of 2020 is the fertility at 21 for the cohort born in 1989. In turn, once a set of age-specific fertility rates for the cohorts who were born up to the year of 2010, it is possible for one to establish an hypothetical set of period age-specific fertility rates which will be needed to project the future population until the year of 2055. The difference in the hypothetical system of age-specific fertility rates between this study and the 2005 special population projection comes from the fact that the fertility estimation/projection model used in this study was skillfully exploited to reflect better actual trend of fertility decline caused by rise in marriage age and increasing proportion of those who remain single until their end of reproduction. In this regard, this paper argues that the set of age-specific fertility rates derived from this study is more logical and reasonably accurate than the set of those used for the 2005 special projection. In the population projection, however, the fundamental issue of the hypothetical setting of age-specific fertility rates in relation to the fertility estimation/projection model is about how skillfully one can handle the period effects. It is not easy for one to completely cope with the problem of period effects except for the a minor period adjustment based on recent actual data, along with the given framework of a cohort-based fertility estimation/projection model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.457-467
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• 2021

This paper aims to analyze changes in urban space use due to social distancing measures for COVID-19 using de facto population data in Seoul during daytime, which is estimated by Seoul Metropolitan Government and telecommunication company of KT using public big data and LTE signal data. The result of kernel density estimation and spatial autocorrelation analysis shows that the distribution patterns of de facto population in 2019 and 2020 were generally similar. This is a result of showing that the government's social distancing measures enabled a certain level of normal activities while suppressing the spread of COVID-19. However, analyzing de facto population subtracting 2019 from 2020 showed different results at the micro level. De facto population decreased in commercial areas but increased in residential areas. This means that COVID-19 social distancing measures had spatially uneven effect. The results of analyzing the effect of regional, land use, economic, educational, and accessibility characteristics on the changes of de facto population using spatial regression analysis are as follows. The higher the density of commercial facilities, the more businesses subject to regulations and schools and universities that require non-face-to-face classes, the more de facto population decreased. Conversely, it was found that de facto population increased in areas with many houses and parks due to telecommuting.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.825-833
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• 2013

An estimation of confidence intervals is essential to calculate uncertainty for greenhouse gases inventory. It is generally assumed that the population has a normal distribution for the confidence interval of parameters. However, in case data distribution is asymmetric, like nonnormal distribution or positively skewness distribution, the traditional estimation method of confidence intervals is not adequate. This study compares two estimation methods of confidence interval; parametric and non-parametric method for exponential distribution as an asymmetric distribution. In simulation study, coverage probability, confidence interval length, and relative bias for the evaluation of the computed confidence intervals. As a result, the chi-square method and the standardized t-bootstrap method are better methods in parametric methods and non-parametric methods respectively.