• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.183-194
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• 2007

The problem of calculating the sample sizes for comparing two independent binomial proportions is studied, when one of two probabilities or both are smaller than 0.05. The use of Whittemore(1981)'s corrected sample size formula for small response probability, which is derived based oB multiple logistic regression, demonstrates much larger sample sizes compared to those by the asymptotic normal method, which is derived for the comparison of response probabilities belonging to the normal range. Therefore, applied statisticians need to be careful in sample size determination with small response probability to ensure intended power during a planning stage of clinical trials. The results of this study describe that the use of the sample size formula in the textbooks might sometimes be risky.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.857-871
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• 2013

Export credit insurance is a policy tool for export growth. In the era of free trade under the governance of WTO, export credit insurance is still allowed as one of the few instruments to increase exports. This paper, using data on short-term export insurance contracts issued to foreign subsidiaries of Korean companies, calculates the expected loss per exposure by combining the effect of risk factors (credit rate of foreign importers, size of mother company, and payment period) on loss frequency and loss severity in different levels. We, applying generalized linear models (GLM), first fit loss frequency and loss severity to negative binomial and lognormal distribution, respectively, and then estimate the loss frequency rate per contract and the ratio of loss severity to coverage amount. Finally, we calculate the expected loss per exposure for each level of risk factors by combining these two rates. Based on the result of statistical analysis, we present the implication for the current premium rate of export insurance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.95-102
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• 2008

This paper presents an appropriate approach for modeling noise in Computed Radiography(CR) images of high strength materials. The approach is specifically designed for types of noise with the statistical and nonlinear properties. CR images Ere degraded even before they are encoded by computer process. Various types of noise often contribute to contaminate radiography image, although they are detected on digitalization. Quantum noise, which is Poisson distributed, is a shot noise, but the photon distribution on Image Plate(IP) of CR system is not always Poisson process. The statistical properties are relative and case-dependant due to its material characteristics. The usual assumption of a distribution of Poisson, binomial and Gaussian statistics are considered. Nonlinear effect is also represented in the process of statistical noise model. It leads to estimate the noise variance in regions from high to low intensity, specifying analytical model. The analysis approach is tested on a database of steel tube step-wedge CR images. The results are available for the comparative parameter studies which measure noise coherence, distribution, signal/noise ratios(SNR) and nonlinear interpolation.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.889-904
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• 2006

Our purpose is to ascertain, if possible, whether atomic bomb survivors with cataracts and epilation were more radiosensitive than those survivors with cataracts but without epilation. A major ophthalmologic survey was conducted in Hiroshima and Nagasaki in 1963-64. At that time, 2125 individuals were examined. Among these individuals, estimated eye organ doses, based on the DS86 dosimetry system, and information on the occurrence of epilation within the first 60 days following the bombings are available on 1742. In the analysis of these data we have assumed that each individual represents a sample of one from a binomial distribution, and that the occurrence of cataracts and epilation are independent biological phenomena. We got following results. The threshold for cataract induction and its 95% confidence limits have been estimated from data on the occurrence of cataract and epilation. Among the 1742 study subjects, 40 had both cataracts and severe epilation. The estimated threshold based on these cases is 0.98 sievert(Sv), with 95% lower and upper confidence bounds of 0.72, and 1.32 Sv, respectively, and is highly statistically significant. Among the 27 cases of cataracts where severe epilation was not reported, the estimated threshold is 1.74 Sv with 95% lower and upper confidence bounds of 1.21 Sv, and "not estimable". The difference between these two estimates is not statistically significant although the effect of dose is highly significant in both instances. The potential importance of biases in the DS86 dose estimates is discussed. The difference between the threshold estimated from cataract cases with epilation and that from cases without epilation is not statistically significant at the 5% or 10% level, and thus affords no support for the notion of increased radiosensitivity.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.177-193
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• 2010

The purpose of this study is to explore normal distribution in probability distributions of the area of statistics in high school mathematics. To do this these contents such as approximation of normal distribution from binomial distribution, investigation of normal distribution curve and the area under its curve through the method of Monte Carlo, linear transformations of normal distribution curve, and various types of normal distribution curves are explored with CAS calculator. It will not be ablt to be attained for the objectives suggested the area of probability distribution in a paper-and-pencil classroom environment from the perspectives of tools of CAS calculator such as trivialization, experimentation, visualization, and concentration. Thus, this study is to explore various properties of normal distribution curve with CAS calculator and derive from pedagogical implications of teaching and learning normal distribution curve.

• Genomics & Informatics
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• v.19 no.1
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.

• Journal of Preventive Medicine and Public Health
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• v.52 no.5
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• pp.308-315
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• 2019

Objectives: Estimating influenza-associated mortality is important since seasonal influenza affects persons of all ages, causing severe illness or death. This study aimed to estimate influenza-associated mortality, considering both periodic changes and age-specific mortality by influenza subtypes. Methods: Using the Microdata Integrated Service from Statistics Korea, we collected weekly mortality data including cause of death. Laboratory surveillance data of respiratory viruses from 2009 to 2016 were obtained from the Korea Centers for Disease Control and Prevention. After adjusting for the annual age-specific population size, we used a negative binomial regression model by age group and influenza subtype. Results: Overall, 1 859 890 deaths were observed and the average rate of influenza virus positivity was 14.7% (standard deviation [SD], 5.8), with the following subtype distribution: A(H1N1), 5.0% (SD, 5.8); A(H3N2), 4.4% (SD, 3.4); and B, 5.3% (SD, 3.7). As a result, among individuals under 65 years old, 6774 (0.51%) all-cause deaths, 2521 (3.05%) respiratory or circulatory deaths, and 1048 (18.23%) influenza or pneumonia deaths were estimated. Among those 65 years of age or older, 30 414 (2.27%) all-cause deaths, 16 411 (3.42%) respiratory or circulatory deaths, and 4906 (6.87%) influenza or pneumonia deaths were estimated. Influenza A(H3N2) virus was the major contributor to influenza-associated all-cause and respiratory or circulatory deaths in both age groups. However, influenza A(H1N1) virus-associated influenza or pneumonia deaths were more common in those under 65 years old. Conclusions: Influenza-associated mortality was substantial during this period, especially in the elderly. By subtype, influenza A(H3N2) virus made the largest contribution to influenza-associated mortality.

• Korean Journal of Clinical Pharmacy
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• v.31 no.4
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• pp.268-277
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• 2021

Background: Most antipsychotic drugs studies have been mainly conducted on side effects, randomized clinical trials, utilization rates, and trends. But there have been few studies on the influencing factors in elderly patients. The purpose of this study was to analyze the influencing factors on the outpatient prescription of antipsychotic drugs in the elderly patients. Methods: Active ingredients of antipsychotic drugs in Korea were selected according to the Korean Pharmaceutical Information Center (KPIC)'s classification. Data source was Korean Health Insurance Review and Assessment Service (HIRA) claims data in 2020 and target patient group was the elderly patient group. We extracted patients who have been prescribed one or more antipsychotic drugs and visited only one medical institution. Data were analyzed using descriptive statistics, chi-square, t-test, negative binomial regression. Results: A number of outpatients were 245,197 and prescriptions were 1,379,092. Most characteristics of patients were 75-85 year's old, female, health insurance type, no disease (dementia, schizophrenia), atypical drugs, cci score (>2) and characteristics of medical institution were neurology in specialty, rural region, general hospitals. Results of regression showed that patient's characteristics and medical center characteristics had significant effect on the outpatient prescription of antipsychotic drugs in the elderly patients. Conclusion: This study suggests that national policy of antipsychotic drugs in the elderly patients, with the consideration of the patients' and medical institutions' characteristics, is needed.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.402-411
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• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

• 한국노년학
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• v.32 no.3
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• pp.777-800
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• 2012

This paper aims to estimate the effects of environmental variables on volunteering among older persons and decide relationships between independent and dependent variables. The thesis conceptually points out that the integrated theory of resources too much emphasizes the important roles of human, social and cultural capital, but overlooks the influences of ecological environments in explaining volunteering among the older persons. And the thesis tries to apply the general ecological theory of aging to explaining volunteering of older people together with resource frameworks, and to estimate the effects of ecological environment variables on volunteerism for senior citizens. Using a micro data of 2009 National Social Survey by Statistics Korea, the paper screens out 10,268 subjects who are believed to socially retire and be above 55 years older. The multiple OLS regression and binomial logistic regression techniques are used to estimate the effects of ecological environments and resources on volunteering. The analysis results show that all of environmental and resource variables are related to volunteering at the level of p<.000. This means that environmental variables have independent effects on the volunteerism, controlling for resource variables. This results suggest that both theories have empirical evidences in explaining volunteerism in Korea. Also, at the end of paper, theoretical and policy implications for practices and future studies are discussed.