• Clinics in Shoulder and Elbow
• /
• 제16권1호
• /
• pp.63-72
• /
• 2013

임상 의학의 연구에 사용되는 대표적 다변량 분석 방법은 다중 회귀 분석 방법인데, 이는 인과 관계를 토대로 여러 개의 변수에 의한 한꺼번에의 영향력을 분석하기 위한 방법이다. 다중 회귀 분석은 기본적으로 회귀 분석의 기본 가정을 만족해야 함은 물론, 여러 개의 독립 변수들이 포함되기 때문에 변수들을 모형에 포함시키는 방법 및 다중 공선성 문제에 대한 고려가 필요하다. 다중 회귀 분석 모형의 설명력은 결정 계수 $R^2$으로 표현되어 1에 가까울수록 설명력이 크며, 각 독립 변수들의 결과에의 영향력은 회귀 계수인 ${\beta}$값으로 표현된다. 다중 회귀 분석은 종속 변수의 형태에 따라 다중 선형 회귀 분석, 다중 로지스틱 회귀 분석, 콕스 회귀 분석으로 나눌 수 있다. 종속 변수가 연속 변수인 경우 다중 선형 회귀 분석, 범주형 변수인 경우 다중 로지스틱 회귀 분석, 시간의 영향을 고려한 상태 변수인 경우는 콕스 회귀 분석을 시행해야 하며, 각각 결과에의 영향력은 회귀 계수 ${\beta}$, 교차비, 위험비로 평가한다. 이러한 다변량 분석에 대한 이해는 연구를 계획하고 결과를 분석하고자 하는 임상 의사에게 있어 보다 효율적인 연구를 위해 필수적인 소양이라고 할 수 있다.

• Asian Pacific Journal of Cancer Prevention
• /
• 제17권sup3호
• /
• pp.113-117
• /
• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• Communications for Statistical Applications and Methods
• /
• 제10권2호
• /
• pp.257-266
• /
• 2003

Distribution-free estimation methods are proposed for slope, $\beta$ in the simple linear regression model. In this paper, we suggest the point estimators using the sequential slope based on sign test and Wilcoxon signed rank test. Also confidence intervals are presented for each estimation methods. Monte Carlo simulation study is carried out to compare the efficiency of these methods with least square method and Theil´s method. Some properties for the proposed methods are discussed.

• 한국응급구조학회지
• /
• 제22권3호
• /
• pp.131-148
• /
• 2018

Purpose: This study examined the associations of job stress and burnout with the quality of life (QOL) among 119 emergency medical technicians (EMTs). Methods: Using a descriptive correlational design, 260 EMTs working in D City or S City completed the questionnaires. Hierarchical multiple regression analysis was conducted to determine the predictors of QOL among 119 EMTs. Results: Overall, there was relatively low job stress among 119 EMTs. There were significant differences in job stress and burnout by general characteristics, especially regarding those of gender, service career, job rank, and self-reported health. In a hierarchical multiple regression, general characteristics explained 29% of QOL (Model I, F=16.369, p<.001). The explanatory power for QOL increased to 49% upon adding job stress (Model II, F=18.737, p<.001), and 59% upon adding burnout (Model III, F=22.621, p<.001). In the last model, self-reported health (${\beta}=.316$, p<.001), job demand (${\beta}=-.130$, p=.009), job insecurity (${\beta}=-.136$, p=.010), lack of reward (${\beta}=-.189$, p=.001), emotional exhaustion (${\beta}=-.196$, p=.004) and lack of personal accomplishment (${\beta}=-.334$, p<.001) were significant predictors of QOL among 119 EMTs. Conclusion: Based on the results, it is necessary to assess and manage job stress and burnout systematically among EMTs, and to develop health improvement programs for better QOL.

• 한국직업건강간호학회지
• /
• 제24권2호
• /
• pp.94-102
• /
• 2015

Purpose: The purpose of this study was to investigate Korean blue-collar workers' Health-related Quality of Life (HRQoL) and influencing factors in Korean blue-collar workers. Methods: Participants in this study were 109 Korean blue-collar workers. The survey included health-related, work-related, and psycho-social factors. SF-36 was used to measure HRQoL. The data were analyzed using Pearson's correlation, and hierarchical multiple regression analysis. Results: In the hierarchical linear regression model, when subjects' psycho-social variables were included in the regression model, $R^2$ change was statistically significant. The significant predictors for HRQoL were education level (${\beta}=.26$, p=.023), depression (${\beta}=-.38$, p<.001), and self-efficacy (${\beta}=.23$, p<.001). Conclusion: The results of this study indicate that health care providers must have priority to consider psycho-social variables, especially depression and self-efficacy to improve HRQoL in Korean blue-collar workers.

• 한국융합학회논문지
• /
• 제10권4호
• /
• pp.237-246
• /
• 2019

본 연구의 목적은 대학생들의 미디어 폭력성 매체 수용 정도, 미디어 폭력성 매체에 대한 현실감 지각과 폭력인식을 파악하고 데이트 폭력 행동에 미치는 영향 요인을 파악하고자 함이다. 대학생 211명을 대상으로 independent t-test, ANOVA, pearson correlation, multiple regression으로 분석하였다. 본 연구에서 데이트 폭력에 영향을 미치는 요인을 살펴보았을 때, 성폭력 영역에서 폭력 정당화(${\beta}=.38$, p<.001), 데이트 관계 신화(${\beta}=.17$, p=.010) 이었으며, 성희롱 영역에서는 폭력 정당화(${\beta}=.48$, p<.001)이었다. 언어 폭력 영역에서는 폭력 정당화(${\beta}=.52$, p<.001), 신체 폭력 영역에서는 폭력 정당화(${\beta}=.48$, p<.001)이었으며 스토킹에서는 폭력 정당화(${\beta}=.38$, p<.001), 데이트 관계 신화(${\beta}=.14$, p=.024)로 나타났다. 본 연구 결과를 토대로 미디어 폭력성의 수용 정도와 매체에 대한 특성을 파악하고, 폭력 정당화의 정도를 낮추고, 데이트 관계 신화의 인식을 개선할 수 있는 교육이 필요하다는 것을 알 수 있다.

• Journal of the Korean Statistical Society
• /
• 제9권1호
• /
• pp.61-77
• /
• 1980

In response surface experiments, a polynomial model is often used to fit the response surface by the method of least squares. However, if the vectors of predictor variables are multicollinear, least squares estimates of the regression parameters have a high probability of being unsatisfactory. Hoerland Kennard have demonstrated that these undesirable effects of multicollinearity can be reduced by using "ridge" estimates in place of the least squares estimates. Ridge regrssion theory in literature has been mainly concerned with selection of k for the first order polynomial regression model and the precision of $\hat{\beta}(k)$, the ridge estimator of regression parameters. The problem considered in this paper is that of selecting k of ridge regression for a given polynomial regression model with an arbitrary order. A criterion is proposed for selection of k in the context of integrated mean square error of fitted responses, and illustrated with an example. Also, a type of admissibility condition is established and proved for the propose criterion.criterion.

• 대한지리학회지
• /
• 제39권2호
• /
• pp.212-228
• /
• 2004

본 연구는 지역간 소득분포의 수렴/발산의 주요 측면인 베타-수렴을 공간자료분석에 의거하여 비판적으로 검토하고 있다. 베타-수렴에 대한 통상적인 접근법은 두 가지 측면에서 문제점을 갖고 있다. 첫째, 회귀분석 결과 도출되는 잔차의 공간적 자기상관을 고려하지 못한다. 둘째, 베타-수렴의 국지적 변이, 즉 공간적 이질성을 탐색할 어떠한 절차도 제공하지 못한다. 이러한 비판적 검토를 바탕으로, 다양한 공간자료분석 기법들, 즉, 공간적 자기회기 모델(spatial autoregressive models), 이변량 국지통지(bivariate local statistics)를 이용한 탐색적 공간자료분석(ESDA: exploratory spatial data analysis) 기법, 그리고 지리적 가중회귀분석(GWR: geographically weighted regression)을 사용하여 1969-1999년 간의 미국 노동시장지역에 대한 소득 자료를 분석하였다. 주요 결과는 다음과 같다. 첫째, OSL모델을 적용한 결과 베타-수렴은 단지 부분적으로만 드러났고, 베타-수렴 계수도 시기별로 상당한 편차를 보였다. 둘째, 공간적 자기회기 모델의 분석 결과 OLS에 의해 유의한 것으로 나타난 베타-수렴 계수가 99% 신뢰수준에서 유의하지 않은 것으로 드러났다. 셋째, 탐색적 공간자료분석과 지리적 가중회귀분석의 결과는 베타-수렴의 경향에 상당한 정도의 공간적 이질성이 존재한다는 점을 보여주고 있다. 또한 이 공간적 이질성의 양상이 시기별로도 다양하게 드러남이 관찰되었다.

• 한국간호교육학회지
• /
• 제14권1호
• /
• pp.73-79
• /
• 2008

Purpose: This study was conducted to investigate the level of nursing professionalism and the factors affecting it, In addition, it can serve as a fundamental resource for development of appropriate strategies for nursing professionalism. Method: This study was performed on 370 nurses working at two university hospitals located in Seoul. Data was analyzed by Pearson correlation analysis, and stepwise multiple regression using SPSS Win 14.0. Result: The estimated regression model of nursing professionalism was statistically significant (F=199.89, p=.000). Major factors influencing nursing professionalism were observed as ability of job performance (${\beta}=.811$), job satisfaction (${\beta}=.140$), organizational commitment (${\beta}=.086$), and turnover intention (${\beta}=.084$). These four factors explained 67.9% of nursing professionalism. Conclusion: Based on the results of the study, further research is needed to investigate other factors affecting nursing professionalism.

• 동서간호학연구지
• /
• 제19권1호
• /
• pp.55-61
• /
• 2013

Purpose: This study was performed to provide basic data for nursing intervention plan to improve health related to task by examining whether nurses' burnout is related with job stress, job satisfaction, social support, and self efficacy in hospitals. Methods: The participants were 320 nurses who work at 5 different university hospitals with individual agreement for this study. The questionnaire were provided to the subjects. Data analysis was done by Pearson correlation coefficient and multiple regression were used. Results: Estimated regression model of burnout of nurses was statistically significant (F=119.88, p<.001). Major factors which affect burnout of nurses were job stress (${\beta}=.54$), job satisfaction (${\beta}=-.31$), and social support (${\beta}=-.20$) which explained 53.4% of burnout of nurse. As a result of examining the assumption of the regression, all results were satisfactory with the assumption of the regression equation. Conclusion: Based on the results of the study, It is nacessary to reduce job stress and increse job satisfaction and social support in order to reduce burnout of nurse. Job stress management may be needed mostly because job stress was the highest level of prediction against burnout.