• Journal of Physiology & Pathology in Korean Medicine
• /
• v.36 no.3
• /
• pp.94-99
• /
• 2022

The discovery of biomarkers related to pattern identification (PI), the core diagnostic theory of Korean medicine (KM), is one of the methods that can provide objective and reliable evidence by applying PI to clinical practice. In this study, 40 diabetic patients and 41 healthy control subjects recruited from the Korean medicine clinic were examined to determine the human electrical response related to the deficiency pattern, a representative pattern of diabetes. Qi-Blood-Yin-Yang deficiency pattern scores, which are representative deficiency patterns for diabetes mellitus, were obtained through a questionnaire with verified reliability and validity, and the human electrical response was measured non-invasively using a bioimpedance meter. In ANCOVA analysis using gender as a covariate, the 5 kHz frequency resistance and 5-250 kHz frequency reactance were significantly lower in the diabetic group than in non-diabetic control group. In addition, the multiple regression analysis showed a positive correlation (R2=0.11~0.19) between the Yang deficiency pattern score and resistance value for the diabetic group; the correlation was higher at higher frequencies of 50kHz (R2=0.18) and 250kHz (R2=0.19) compared to 5kHz(R2=0.11). In contrast, there was no such significant association in the control group. It implies that bioimpedance resistance measured at finite frequencies may be useful in predicting Yang deficiency, which is closely related to diabetic complications by reflecting the decrease in body water content and metabolism. In the future, large-scale planned clinical studies will be needed to identify biomarkers associated with different types of PI in diabetes.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.10a
• /
• pp.40-43
• /
• 2000

In this paper, we investigate how the average survival time of listed companies in the Korea Stock Exchange (KSE) are affected by changes in macro-economic environment and covariate vectors which show peculiar financial characteristics of each company. We also apply the survival analysis approach to the dichotomous firm failure prediction and the results show a similar pattern of forecasting performance using the existing dichotomous prediction techniques. These findings suggest that, when we consider a bankruptcy model under a certain economic event, the survival approach can be a useful alternative to the existing dichotomous prediction methods since the approach provides estimation of average survival time as well as simple binary prediction.

• Journal of Preventive Medicine and Public Health
• /
• v.31 no.1 s.60
• /
• pp.72-81
• /
• 1998

The purpose of this study was to investigate the relation between health behavior patterns and demographic, socio-economic characteristics, health status, health information in Korea. The quantification method through canonical correlation analysis was conducted to the data from Korea National Health Survey in 1995, which consisted of 5,805 persons. The health lifestyle patterns were quantified as good diet lifestyle, passive lifestyle to the negative direction and drinker lifestyle, smoker lifestyle, hedonic lifestyle and fitness lifestyle to the positive direction. The covariate were related to health lifestyle patterns in the order of sex, age, marital status, occupation, health information, economic status, level of physical labour and health status. Characteristics of male, age below 50, married, blue colored worker, no health information, low in economic status, heavy level of physical labour, and poor in health status were positively related to drinker lifestyle, smoker lifestyle, hedonic lifestyle, fitness lifestyle sequentially.

• Journal of the Korean Data and Information Science Society
• /
• v.15 no.2
• /
• pp.367-378
• /
• 2004

Recently logistic regression is popular in a variety of fields so that a number of statistical packages are developed for analyzing the logistic regression. This paper briefly considers the several types of logistic regression models used depending on different types of data. In addition, when four statistical packages (MINTAB, SAS, SPSS and STATA) are used to apply logistic regression models to the real fields respectively, their scope and characteristics are investigated.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.6
• /
• pp.1465-1475
• /
• 2013

The chi-square type test statistic is the most commonly used test in terms of measuring testing goodness-of-fit for multinomial logistic regression model, which has its grouped data (binomial data) and ungrouped (binary) data classified by a covariate pattern. Chi-square type statistic is not a satisfactory gauge, however, because the ungrouped Pearson chi-square statistic does not adhere well to the chi-square statistic and the ungrouped Pearson chi-square statistic is also not a satisfactory form of measurement in itself. Currently, goodness-of-fit in the ordinal setting is often assessed using the Pearson chi-square statistic and deviance tests. These tests involve creating a contingency table in which rows consist of all possible cross-classifications of the model covariates, and columns consist of the levels of the ordinal response. I examined goodness-of-fit tests for a proportional odds logistic regression model-the most commonly used regression model for an ordinal response variable. Using a simulation study, I investigated the distribution and power properties of this test and compared these with those of three other goodness-of-fit tests. The new test had lower power than the existing tests; however, it was able to detect a greater number of the different types of lack of fit considered in this study. I illustrated the ability of the tests to detect lack of fit using a study of aftercare decisions for psychiatrically hospitalized adolescents.

• The Korean Journal of Applied Statistics
• /
• v.16 no.2
• /
• pp.407-426
• /
• 2003

We consider the missing covariates problem in generalized estimating equations(GEE) model. If the covariate is partially missing, GEE can not be calculated. In this paper, we study the performance of 7 imputation methods to handle missing covariates in GEE models, and the properties of GEE estimators are investigated after missing covariates are imputed for ordinal data of repeated measurements. The 7 imputation methods include i) Naive Deletion ii) Sample Average Imputation iii) Row Average Imputation iv) Cross-wave Regression Imputation v) Carry-over Imputation vi) Bayesian Bootstrap vii) Approximate Bayesian Bootstrap. A Monte-Carlo simulation is used to compare the performance of these methods. For the missing mechanism generating the missing data, we assume ignorable nonresponse. Furthermore, we generate missing covariates with or without considering wave nonresp onse patterns.

• Safety and Health at Work
• /
• v.13 no.3
• /
• pp.294-301
• /
• 2022

Background: In the early stage of the coronavirus disease 2019 (COVID-19) epidemic, small- and midsized enterprises (SMEs) may be an important transmission consideration. The study aimed to identify the pattern of COVID-19 prevention measures during the outbreaks in Daegu and Gyeongsangbuk-do at the early stage of COVID-19. Moreover, we investigated whether SME size and past experiences affected the preventive measures implemented in the region. Methods: A survey detailing the general characteristics and implementation of 12 preventive activities was conducted in 122 SMEs in Daegu and Gyeongsangbuk-do. The survey was analyzed by size and operation period. Results: The study subjects consisted of 53 (43.4%) workplaces with 1-5 employees, 50 (40.9%) workplaces with 6-30 employees, and 19 (15.6%) workplaces with 31-49 employees. The lowest three items among those surveyed were 'symptomatic workers to stay home for 3-4 days' (17.2%), 'work remotely' (18.9%), and 'video meetings' (20.5%). There were significant differences in the rate of several preventive measures implemented. The larger sized SMEs, the higher the number of implementations (p < 0.01). The operation period had no significant relationship with the implementation of preventive measures. The same pattern was observed in multiple generalized linear regression with covariate adjustment. Conclusion: Preventive measures among SMEs with fewer than 50 employees were identified. Even within SMEs, a gap in preventive measures according to size was confirmed. To prevent the spread of infection and protect workers' right to health, different support for different sized SMEs is necessary.

• Korean Journal of Psychosomatic Medicine
• /
• v.8 no.2
• /
• pp.165-171
• /
• 2000

Objectives : Alopecia areata has been known to be closely related to stress. The purpose of this study is to examine the relationship between stress and alopecia areata investigating how life events(which alopecia areata patients experience), amount of stress, coping strategy, and their personality type affect the oneset and aggravation of the disease. Methods : The subjects were 43 alopecia areata patients who visited the department of dermatology outpatients clinic, and 36 fungal infection diseases patients as the control group. They all completed Scale of Life Events, Coping Style Cheklist, Eysenck A-type Personality Inventory. The analysis of covariance with the age as covariate was carried out. Results : Compared to the control group, alopecia areata patients had significantly more stressful life events, and higher amount of stress, but there was no significant difference in coping strategy. Type A Personality is also resulted to have no significant relationship to alopecia areata. Conclusions : Alopecia areata patients had significantly higher amount of stress than the control group, and this result is consistent with the previous studies which suggest that stress contributes to the oneset of alopecia areata. The causual relationship between stress and alopecia areata should be further examined in order to be applied in clinical setting.

• Asian-Australasian Journal of Animal Sciences
• /
• v.26 no.9
• /
• pp.1237-1246
• /
• 2013

The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade $B{\times}F$ cows (3/16B 13/16F) had the highest least squares means (LSM) for LY ($2,490{\pm}178.9kg$), IY ($10.5{\pm}0.8kg$), PY ($12.7{\pm}0.9kg$), YD ($7.6{\pm}0.55kg$) and LL ($361.4{\pm}31.2d$), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability ($0.03{\pm}0.03$ and $0.08{\pm}0.02$) and repeatability ($0.14{\pm}0.01$ to $0.24{\pm}0.02$) estimates for LL, DP and parameter c. Medium heritability ($0.21{\pm}0.03$ to $0.33{\pm}0.04$) and repeatability ($0.27{\pm}0.02$ to $0.53{\pm}0.01$) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman's rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population.

• 재활복지
• /
• v.18 no.4
• /
• pp.279-293
• /
• 2014

The purpose of the study was to investigate the effects of task presentation methods (animation vs. picture) on verb naming abilities as a function of verb argument structures for normal elderly adults. Participants were categorized into the two groups: animation group(n=21) vs. picture group(n=21). Data for the animation group were from obtained from Sung and Choi (2012). Percent of accuracy for the verb naming task served as a dependent measure for statistical analyses. After the years of education was controlled as a covariate, a two-way mixed ANOVA was performed with the group as a between-subject factor and the argument structure(1-, 2-, and 3-place) as a within-subject factor. Results revealed that there was a significant interaction between the group and argument structure, whereas there were no main effects for either of the factors. The animation group performed better than the picture group for one-place verb, whereas the opposite pattern was observed for the three-place verbs. The results suggested that the presentation methods are one of the critical factors that influenced verb naming abilities in elderly adults.