• Journal of the Korean Data and Information Science Society
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• 제28권4호
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• pp.937-945
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• 2017

The purpose of using a control chart is to detect any change that occurs in the process. When control charts are used to monitor processes, we want to identify this changes as quickly as possible. Many problems in quality control involve a vector of observations of several characteristics rather than a single characteristic. Multivariate CUSUM or EWMA charts have been developed to address the problem of monitoring covariance matrix or the joint monitoring of mean vector and covariance matrix. However, control charts tend to work poorly when we use the highly correlatted variables. In order to overcome it, Hawkins (1991) proposed the use of regression adjustment variables. In this paper, to monitor covariance matrix, we investigate the performance of MEWMA-type control charts with and without the use of regression adjusted variables.

• 대한간호학회지
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• 제28권2호
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• pp.256-269
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• 1998

The purpose of this study was to evaluate the usefulness of variables which were known to be related to blood pressure for discriminating between hypertensive and normotensive groups. Variables were obesity, serum lipids, life style-related variables such as smoking, alcohol, exercise, and stress, and demographic variables such as age, economical status, and education. The data were collected from 400 male clients who visited one university hospital located in Incheon, Republic of Korea, from May 1996 to December 1996 for a regular physical examination. Variables which showed significance for discriminating systolic blood pressure in this study were age, serum lipids, education, HDL, exercise, total cholesterol, body fat percent, alcohol, stress, and smoking(in order of significance). By using the combination of these variables, the possibility of proper prediction for a high-systolic pressure group was 2%, predicting a normal-systolic pressure group was 70.3%, and total Hit Ratio was 70%. Variables which showed significance for discriminating diastolic blood pressure were exercise, triglyceride, alcohol, smoking, economical status, age, and BMI (in order of significance). By using the combination of these variables, the possibility of proper prediction for a high-diastolic pressure group was 71.2%, predicting a normal-diastolic pressure group was 71.3%, and total Hit Ratio was 71.3%. Multiple regression analysis was performed to examine the association of systolic blood pressure with life style-related variables after adjustment for obesity, serum lipids, and demographic variables. First, the effect of demographic variable alone on the systolic blood pressure was statistically significant (p=.000) and adjusted $R^2$was 0.09. Adding the variable obesity on demographic variables resulted in raising adjusted $R^2$to 0.11 (p=.000) : therefore, the contribution rate of obesity on the systolic blood pressure was 2.0%. On the next step, adding the variable serum lipids on the obesity and demographic variables resulted in raising adjusted R2 to 0.12(P=.000) : therefore, the contribution rate of serum lipid on the systolic pressure was 1.0%. Finally, adding life style-related variables on all other variables resulted in raising the adjusted $R^2$to 0.18(p=.000) ; therefore, the contribution rate of life style-related variables on the systolic blood pressure after adjustment for obesity, serum lipids, and demographic variables was 6.0%. Multiple regression analysis was also performed to examine the association of diastolic blood pressure with life style-related variables after adjustment for obesity, serum lipids, and demographic variables. First, the effect of demographic variable alone on the diastolic blood pressure was statistically significant (p=.01) and adjusted $R^2$was 0.03. Adding the variable obesity on demographic variables resulted in raising adjusted $R^2$to 0.06 (p=.000) ; therefore, the contribution rate of obesity on the diastolic blood pressure was 3.0%. On the next step, adding the variable serum lipids on the obesity and demographic variables resulted in raising the adjusted $R^2$ to 0.09(p=.000) ; therefore, the contribution rate of serum lipid on the diastolic pressure was 3.0%. Finally, adding life style-related variables on all other variables resulted in raising the adjusted $R^2$ to 0.12 (p=.000) : therefore, the contribution rate of life style-related variables on the systolic blood pressure after adjustment for obesity, serum lipids, and demographic variables was 3.0%.

• 운동영양학회지
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• 제25권1호
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• pp.35-41
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• 2021

[Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R²) and 85.9% (adjusted R²), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R²) and 82.6% (adjusted R²), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R²) and 91.0% (adjusted R²), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

• 보건행정학회지
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• 제13권3호
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• pp.129-147
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• 2003

This study is to grasp a trend of profitability classified by characteristics of hospitals and to analyze related factors. Subjects are 145 hospitals which have gotten the standardization audit by Korean Hospital Association during 1998-200l. Profitability was measured in the aspect of operation profit rate with operating margin to gross revenue as proxy variables. Independent variables were classified by general factors (ownership, number of beds, period of establishment, competition), financial factors (liabilities to total assets, current ratio, fixed ratio, total asset turnover, inventories turnover), and factors related to patient treatment (average length of stay, bed occupancy rate, new outpatient ratio, admission ratio of outpatients, number of patients per specialist, personnel costs per adjusted inpatient, administrative costs per adjusted inpatient). Hierarchical multiple regression analysis model was used in this study. As a result of hierarchical multiple regression analyzation of operating margin to gross revenue, adjustive $R^2$ of general factors was relatively more powerful. The factors had significant effect on operating margin to gross revenue were ownership(+), number of beds(+), competition(+), current ratio(+), fixed ratio(+), total asset turnover(+), personnel costs per adjusted inpatient(-).

• 보건행정학회지
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• 제26권1호
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• pp.30-38
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• 2016

Background: This study purposed to analyze the relationship between spatial distribution of Diabetes prevalence rates and regional variables. Methods: The unit of analysis was administrative districts of city gun gu. Dependent variable was the age- and sex- adjusted diabetes prevalence rates and regional variables were selected to represent three aspects: demographic and socioeconomic factor, health and medical factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis, geographically weighted regression (GWR) was applied for the spatial analysis. Results: Analysis results showed that age- and sex-adjusted diabetes prevalence rates were varied depending on regions. OLS regression showed that diabetes prevalence rates had significant relationships with percent of population over age 65 and financial independence rate. In GWR, the effects of regional variables were not consistent. These results provide information to health policy makers. Conclusion: Regional characteristics should be considered in allocating health resources and developing health related programs for the regional disease management.

• 운동영양학회지
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• 제24권1호
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• pp.9-13
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• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• 재무관리연구
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• 제6권2호
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• pp.33-69
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• 1989

The Purpose of this study is to test empirically the determinants of capital structure of the Korea Listed Firms. In order to accomplish the purpose of this study, both literature survey and empirical test have been made. For the empirical test, agency and asymmetric information factors as well as traditional ones have been throughly reviewed. Traditional factors tested in this study include firm-size, collateral value of the assets, business risk, tax, non-debt tax shields, and industry effects. Agency and asymmetric information factors include growth opportunities, the percentage of outstanding equity held by inside stockholders, and the number of inside stockholders. From the results of the cross-sectional regression analysis, the adjusted R-square is 1931%, and the overall F-value indicates significance. For the analysis period, the signs of the variables except business risk are as predicted. Firm-size, collateral value of the assets, and business risk significant at the.01-.05 level. In order to determine the influence of industry factors on the financial leverage, a total of 8 dummy variables are added to the regression model. The adjusted R-square inclosed by 4.2% for the first analysis period(1983-1985) and 6% for the second analysis period(1986-1987). This suggests that industry factors are significant in explaining the variations in financial leverage across firms. In order to pursue the influence of agency and asymmetric information factors on the financial leverage, again the cross-sectional regression analysis is done for the middle size firms gruop(n=40). The adjusted R-square increased by 9.8% for the first analysis period(1983-1985) and 6.1% for the total analysis period(1983-1987), and all the signs was as predicted. But both the variables except the number of inside stockholders was not significant.

• 한국대기환경학회지
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• 제19권5호
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• pp.561-568
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• 2003

Surface ozone concentrations are highly sensitive to meteorological variability. Therefore, in order to reveal the long-term changes in ozone due to the changes in precursor emissions, we need to remove the effects of meteorological fluctuations on the annual distribution of surface ozone. In this paper, the meteorologically adjusted trends of daily maximum surface ozone concentrations in two major Korean cities (Seoul and Busan) are investigated based on ozone data from 11 (Seoul) and 6 (Busan) sites over the period 1992 ∼ 2000. The original time series consisting of the logarithm of daily maximum ozone concentrations are splitted into long-term, seasonal and short-term component using Kolmogorov-Zurbenko (KZ) filter. Meteorological effects are removed from filtered ozone series using multiple linear regression based on meteorologcial variables. The long-term evolution of ozone forming capability due to changes in precursor emission can be obtained applying the KZ filter to the residuals of the regression. The results indicated that meteorologically adjusted long-term daily maximum ozone concentrations had a significant upward trend (Seoul: ＋ 3.02% yr$^{-1}$ , Busan: ＋ 3.45% yr$^{-1}$ ). These changes of meteorologically adjusted ozone concentrations represent the effects of changing background ozone concentrations as well as the more localized changes in emissions.

• 보건행정학회지
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• 제26권4호
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• pp.271-278
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• 2016

Background: This study purposed to analyze the relationship between regional obesity rates and regional variables. Methods: Data was collected from the Korean Statistical Information Service (KOSIS) and Community Health Survey in 2012. The units of analysis were administrative districts such as city, county, and district. The dependent variable was the age-sex adjusted regional obesity rates. The independent variables were selected to represent four aspects of regions: health behaviour factor, psychological factor, socio-economic factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis model, this study applied geographically weighted regression (GWR) analysis to calculate the regression coefficients for each region. Results: The OLS results showed that there were significant differences in regional obesity rates in high-risk drinking, walking, depression, and financial independence. The GWR results showed that the size of regression coefficients in independent variables was differed by regions. Conclusion: Our results can help in providing useful information for health policy makers. Regional characteristics should be considered when allocating health resources and developing health-related programs.

• 한국병원경영학회지
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• 제10권1호
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• pp.71-92
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• 2005

The purpose of this study is to analyze the efficiency in management of general hospitals and investigate the major factors on efficiency. Specifically, the management of each general hospital is evaluated by using Data Envelopment Analysis(DEA) technique which is a nonparametric statistical method for measurement of efficiency. Then, the influencing factors are investigated through analyses of Decision-Tree Model and Tobit Regression. The target hospitals were general hospitals in which bed sizes are between 200 and 500 among a total of 276 general hospitals. The main data of financial indicators were collected from 48 hospitals, and it was analyzed by using two statistical models. For Model I, three input and two output variables were used for efficiency evaluation. In particular, three input variables were the number of medical doctors, the number of paramedical personnel, and the bed size. And, two output variables were the numbers of inpatients and outpatients per year, adjusted by bed-size. The results of DEA analysis showed that only seven out of 48 hospitals(15%) turned out to be efficient. The decision-tree analysis also showed that there were six significant influencing factors for Model I. Six factors for Model I were Bed Occupancy Rate, Cost per Adjusted Inpatient, New Visit Ratio of Outpatients, Retired Ratio, Net Profit to Gross Revenues, Net Profit to Total Assets. In addition, the management efficiency of hospital is proved to increase as profit and patient-induced indicators increase and cost-related indicators decrease, by the Tobit regression model of independent variables derived from the decision-tree analysis. This study may be contributable to the development of analytic methodology regarding the efficiency of hospital management in that it suggests the synthetic measures by utilizing DEA model instead of suggesting simple ratio-analyzing results.