• 성인간호학회지
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• 제17권5호
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• pp.783-792
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• 2005

Purpose: This study was conducted to meta-analyze the effects of hardiness on health-related variables. Method: After review of 19 studies performed by Korean nurses, research variables, statistical data(r or F), and other methodological data were extracted and coded. Research variables were categorized under 5 groups such as health-related behavior, well-being, adaptation, stress, and support according to conceptual similarity. Using SAS program, 20 research variables and 34 effect sizes were calculated after eliminating heterogeneous data by Q-test, Results: Effects of hardiness on whole research variables was .512 and ranged from .322 to .643 by categories. The greatest effect was obtained from well-being category, whereas the smallest effect from stress category. All effect sizes were statistically significant. But fail-safe numbers were small and failed to achieve reasonable tolerance level. Conclusion: Results of meta-analysis indicated that hardiness has a moderate effect on health-related variables. But for improving the reliability of the results by minimizing publication bias, the more hardiness studies should be done.

• 대한가정학회지
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• 제44권12호
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• pp.53-64
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• 2006

The purpose of this study was to investigate the variables on employees' retirement expectations divided into imposed frustration, new beginning, transition to rest, and continuing. Independent variables were individual(gender, age, occupation, income, education, and health condition), psychological(self-esteem, locus of control, attitude of leisure, and attitude of family), and job-related variables(job attitude, job satisfaction, and job stability). In order to achieve this purpose, a survey was conducted with 515 employees from Daegu and Kyungpook. Retirement expectations were measured with questionnaire based on several studies. The data analyzed by frequency, percentage, mean, factor analysis, Cronbach's $\alpha$, correlation, and multiple regression. The major findings were as follows. First, imposed frustration was affected by income, self-esteem, locus of control, job satisfaction, job attitude, and job stability. Second, new beginning was affected by self-esteem, locus of control, attitude toward leisure and family, and job stability. Individual variables were not statistically significant predictors of new beginning. Third, transition to rest was affected by locus of control, attitude toward family, job satisfaction, job attitude, and job stability. Individual variables were not statistically significant predictors of transition to rest. Finally, continuing was affected by age, education, job satisfaction. Psychological variables were not statistically significant predictors of continuing.

• 보건행정학회지
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• 제4권2호
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• pp.58-76
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• 1994

In order to study factors affecting the use of the ambulatory physician services. Andersen's model for health utilization was modified by adding the health behavior component and examined with three different approaches. Three different approaches were the multiople regression model, logistic regression model, and LISREL model. For multiple regression, dependent variable was reported illness-related visits to a physician during past one year and independent variables are variaous variables measuring predisposing factor, enabling factor, need factor and health behavior. For the logistic regression, dependent variable was visit or no-visit to a physician during past one year and independent variables were same as the multiple regression analysis. For the LISREL, five endogenous variables of health utiliztion, predisposing factor, enabling factor, need factor, and health behavior and 20 exogeneous variables which measures five endogenous variables were used. According to the multiple regression analysis, chronic illness, health status, perceived health status of the need factor; residence, sex, age, marital status, education of the predisposing factor ; health insurance, usual source for medical care of enabling factor were the siginificant exploratory variables for the health utilization. Out of the logistic regression analysis, health status, chronic illness, residence, marital status, education, drinking, use of health aid were found to be significant exploratory variables. From LISREL, need factor affect utilization most following by predisposing factor, enabling factor and health behavior. For LISREL model, age, education, and residence for predisposing factor; health status, chronic illess, and perceived health status for need factor; medical insurance for enabling factor; and doing any kind of health behavior for the health behavior were found as the significant observed variables for each theoretical 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%.

• 대한간호학회지
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• 제23권1호
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• pp.130-141
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• 1993

This study was to find out variables influenced on the medication patterns (voluntary medication, in-voluntary medication) of antipsychotics taken by schizophrenic outpatients. Purposes of this study were to be identified that there was the significant difference between the group of voluntary medication and involuntary, and that which variables had infuence on outpsychotics medication. The sample consisted of 30 patients takeing their pills voluntary (voluntary medication group), and 15 patients involuntary(involuntary medication group) at a psychiatry hospital and a psychiatric unit of a The findings of the study are as follows : university hospital in Daegu. Data were collected from September to October, 1991 through interview using questionare about antipsychotics medication. Data were analyzed by the technique of two group discriminant function analysis using SPSS pc$^{+}$ 1) Discriminant function discriminating between voluntary medication and involuntary medication was significant at the level of 10% significance (sig.=.055, p〈.10) Hit-ratio was very high (91. 1％) 2) One of General variables, SEX, was significant of discriminating between two medication patterns at the level of 10% significance. 3) One of Family Environmental Variables, BROTH(a number of brother), were significant between two medication patterns. (p〈.10) 4) One of Therapeutic Environmental Variables, FAMHX, was significant between two medication patterns at the level of 10% significance. 5) One of Variables Related to Drug and Medication, NECESS, was significant between two medication patterns. (p〈.05) 6) Variables Related to Disease was not significant between two medication patterns.s.

• 품질경영학회지
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• 제34권2호
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• pp.129-135
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• 2006

In the advance of computer technology, it is possible to keep all the related informations for monitoring equipments in control and huge amount of real time manufacturing data in a data base. Thus, the statistical analysis of large data sets with hundreds of thousands observations and hundred of independent variables whose some of values are missing at many observations is needed even though it is a formidable computational task. A tree structured approach to classification is capable of screening important independent variables and their interactions. In a Six Sigma project handling large amount of manufacturing data, one of the goals is to screen vital few variables among trivial many variables. In this paper we have reviewed and summarized CART, C4.5 and CHAID algorithms and proposed a simple method of screening vital few variables by selecting common variables screened by all the three algorithms. Also how to develop a logistics regression model on a large data set is discussed and illustrated through a large finance data set collected by a credit bureau for th purpose of predicting the bankruptcy of the company.

• 품질경영학회지
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• 제40권3호
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• pp.347-358
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• 2012

Purpose: Given the mixture components - process variables experimental data, we propose the strategy to find the proper combined model. Methods: Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components - process variables experiments depend on the mixture components - process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. Results: First we choose the reasonable starting models among the class of admissible product models and practical combined models suggested by Lim(2011) based on the model selection criteria and then, search for candidate models which are subset models of the starting model by the sequential variables selection method or all possible regressions procedure. Conclusion: Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. The strategy to find the proper combined model is illustrated with examples in this paper.

• 아동학회지
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• 제14권2호
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• pp.115-135
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• 1993

The purpose of this study was to develop instruments for measuring paternal child rearing involvement. A second purpose was to investigate the relationship between social competency of child and the father's involvement in child rearing. Fathers' child rearing involvement inventories were administered to 513 5th and 6th grade school students to evaluate children's perceived father's rearing involvement. Assessment of the child's social competency by the mother was by the modified Iowa Social Competency Scale. Data were analyzed by factor analysis, Pearson's correlation coefficient, and canonical correlation. The main results were as follows: (1) There were differences in mean scores between variables on father's child rearing involvement. The mean score of 'day-to-day guidance' was higher than such father's involvement variables as 'family activities', 'household affairs', 'home education'. (2) There was a significant correlation between the social competency of children and father's child rearing involvement. In other words, fathers' child rearing involvement showed significant correlations with 'the capability' and 'leadership' of children. (3) The canonical analysis in two variables-the fathers' child rearing involvement (independent variables) and the children's social competency (dependent variables)-showed that the child variables most highly correlated to the independent variables were 'capability' and 'affection toward parents'. This also indicated that the father variables accounted for about 9.4% of the variation in social competency. In conclusion, the father's child rearing involvement can he recognized as significant variable in predicting the social competency of children.

• Communications for Statistical Applications and Methods
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• 제21권2호
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• pp.161-168
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• 2014

In mixture experiments with process variables, we consider the case that some of process variables are either uncontrollable or hard to control, which are called noise variables. Given the such mixture experimental data with process variables, first we study how to search for candidate models. Good candidate models are screened by the sequential variables selection method and checking the residual plots for the validity of the model assumption. Two methods, which use numerical optimization methods proposed by Derringer and Suich (1980) and minimization of the weighted expected loss, are proposed to find a cost-effective robust optimal condition in which the performance of the mean as well as the variance of the response for each of the candidate models is well-behaved under the cost restriction of the mixture. The proposed methods are illustrated with the well known fish patties texture example described by Cornell (2002).

• 한국과학교육학회지
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• 제31권1호
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• pp.32-47
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• 2011

본 연구에서는 학생들의 변인 통제 논리력과 변인 통제 활동을 분석하고자 하였다. 이를 위해 먼저 변인 통제 능력에 대한 구체적인 채점 기준을 개발하였다. 이어서, 중학교 2학년에 재학 중인 30명의 학생을 대상으로 학생들의 변인 통제 유형을 알아보았다. '계단 빨리 왕복하기'전략을 설계하도록 하는 과제를 부여한 후 얻어진 학생들의 응답 내용을 바탕으로 변인 통제 유형을 분석하였다. 변인 통제의 필요성 인식 여부, 불필요 변인의 배제 여부, 통제 변인의 설계 여부, 조작 변인과 종속 변인의 설계 여부의 네 가지 측면에 따라 유형A~유형F의 여섯 가지 유형으로 분류하였다. 그리고 Lawson의 과학적 사고 수준 검사 문항 중 변인 통제 논리에 해당하는 4개 문항에 대한 답변을 본 연구에서 개발한 채점 기준으로 채점하여 변인 통제 논리력을 측정하였다. Lawson이 개발한 과학적 사고 검사지로 측정한 점수와 변인 통제 논리력 점수의 상관 계수는 .67로 과학적 사고력와 변인 통제 논리력의 상관은 높은 것으로 나타났다(p<.01). 이는 본 연구에서 개발한 채점 기준이 학생들의 변인 통제 능력을 객관적으로 평가할 수 있다고 판단할 수 있으며, 또한 학생들의 과학적 사고력을 측정하는데 이용할 수 있음을 의미하는 것이다.