• Korean Journal of Child Studies
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• v.32 no.3
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• pp.107-120
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• 2011

This study examined the influences of stress and academic self-efficacy on subjective well-being. The subjects were 191 4th-graders and 250 6th-graders. Data were analyzed by means of two-way ANOVA, Pearson's coefficients, and stepwise regression. Results indicated that : (1) There were age or gender differences for stress, academic self-efficacy, and subjective well-being. (2) Stress was negatively correlated with academic self-efficacy and subjective well-being, whereas academic self-efficacy was positively correlated with subjective well-being. (3) Stress and academic self-efficacy explained 43% of subjective well-being. Specifically, stress from parents was the most influential variable for positive affects, and self-regulatory efficacy was the most influential variable for positive efficacy and inter-relatedness.

• Journal of Preventive Medicine and Public Health
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• v.15 no.1
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• pp.213-217
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• 1982

Self sensing symptoms were. surveyed by interview from the workers using lacquer-thinner(Male 35, Female 28). And the data was converted to point. Independent variables were state of the medication, education, alcohol drinking, smoking, living and past occupational history. Dependent variable was the point. The relationship between independent variables and the depenent variable was studied. The result of the study were briefly summarized as below. 1. The difference of point between sex and medication statement was significant by statistical test. 2. Age and past occupational history were not important variables. 3. The Multiple Stepwise Regression Equation obtained by this study was not useful.

• Journal of the Korean Home Economics Association
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• v.42 no.7
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• pp.119-129
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• 2004

The main purpose of this study was to examine the effects of maternal materialism and parenting on materialism in adolescents. Moreover, the relative significance of maternal materialism and parenting materialism in adolescents was also explored. The study subjects were 199 (98 male, 101 female) high school students in Seoul and their mothers. The following are the major findings. 1) Maternal materialism was not related with male adolescents' materialism but was with female adolescents'. 2) Maternal support, and open communication were negatively related with female adolescents' materialism while maternal control, and permissiveness were positively related. On the other hand, only maternal control was positively related with male adolescents' materialism. 3) Stepwise regression analysis revealed that maternal support, followed by maternal materialism, was the most important variable affecting female adolescents'. However, for male adolescents, maternal control was the only one variable affecting their materialism.

• Korean Journal of Social Welfare
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• v.42
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• pp.83-106
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• 2000

The purpose of this study is to identify the common factors that affect adolescents, drinking and delinquency. Previous studies have supported that parenting is the most important variable to explain adolescents' drinking and delinquency. For study, 497 adolescents from middle schools and high schools in Inchon city, Korea, were recruited. Instrument for measurement consists of affective-tie and supervision regarding parenting, drinking, and delinquency. Stepwise multiple regression was used as a main statistical analysis. According to the results, even though there is some association between drinking and delinquency, this study found that the most strong predictable variable in explaining adolescents' drinking and delinquency is parenting. That is to say, effective parenting can contribute to prevent adolescents's drinking and delinquency. Therefore, this study suggests that social services and programs to support effective parenting should be provided.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.79-89
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• 2019

Classification models pertaining to receiver operating characteristic (ROC) curve analysis have been extended from univariate to multivariate setup by linearly combining available multiple markers. One such classification model is the multivariate ROC curve analysis. However, not all markers contribute in a real scenario and may mask the contribution of other markers in classifying the individuals/objects. This paper addresses this issue by developing an algorithm that helps in identifying the important markers that are significant and true contributors. The proposed variable selection framework is supported by real datasets and a simulation study, it is shown to provide insight about the individual marker's significance in providing a classifier rule/linear combination with good extent of classification.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.5
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• pp.539-547
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• 1997

This study was carried out to identify how soybean seed protein concentration is influenced by climatic factors. Twelve lines selected for seed protein concentration were studied in 13 environments of North Carolina. Sensitivity of seed protein concentration, total seed protein, and seed yield to climatic variables was investigated using a linear regression model. Best response models were determined using two stepwise selection methods, Maximum R-square and Stepwise Selection. There were wide climatic effects in seed protein concentration, total protein and seed yield. The highest protein concentration environment was characterized by the most high temperature days(HTD) and the smallest variance of average daily temperature range (VADTRg), while the lowest protein concentration environment was distinguished by the fewest HTD and the largest VADTRg. For protein concentration, all lines responded positively to average maximum daily temperature(MxDT), HTD, and average daily temperature range(ADTRg) and negatively to ADRa, while they responded positively or negatively to average daily temperature(ADT), variance of average minimum daily temperature (VMnDT), and VADTRg, indicating that genotypes may greatly differ in degrees of sensitivity to each climatic variable. Eleven lines seemed to have best response models with 2 or 3 variables. Exceptionally, NC106 did not show a significant sensitivity to any climatic variable and thus did not have a best response model. This indicates that it may be considered phenotypically more stable. For total seed protein and seed yield, all the lines responded negatively to both ADTRg and VADRa, suggesting that synthesis of seed components may increase with less daily temperature range and less variation in daily rainfall.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.435-449
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• 1998

In this article we have introduced a Bayes criterion for the variable selection in multiple discriminant analysis (MDA). The criterion is a default Bayes factor for the comparision of homo/heteroscadasticity of the multivariate normal means. The default Bayes factor is obtained from a development of the imaginary training sample method introduced by Spiegelhalter and Smith (1982). Based an the criterion, we also provided a test for additional discrimination in MDA. The advantage of the criterion is that it is not only applicable for the optimal subset selection method but for the stepwise method. More over, the criterion can be reduced to that for two-group discriminant analysis. Thus the criterion can be regarded as an unified alternative to variable selection criteria suggested by various sampling theory approaches. To illustrate the performance of the criterion, a numerical study has bean done via Monte Carlo experiment.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.435-443
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• 2005

Coefficients of determination in logistic regression analysis are defined as various statistics, and their values are relatively smaller than those for linear regression model. These coefficients of determination are not generally used to evaluate and diagnose logistic regression model. Liao and McGee (2003) proposed two adjusted coefficients of determination which are robust at the addition of inappropriate predictors and the variation of sample size. In this work, these adjusted coefficients of determination are applied to variable selection method for logistic regression model and compared with results of other methods such as the forward selection, backward elimination, stepwise selection, and AIC statistic.

• Journal of Family Resource Management and Policy Review
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• v.1 no.2
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• pp.1-15
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• 1997

The purpose of this study is to investigate (1)the level of the urban housewives’behavior and satisfaction of wedding, (2)the influential factors related to the two dependent variables above mentioned. So that provides some fundamental materials to improve the level of sound wedding culture and the whole home living. The subjects were 356 housewives, in April, 1997, Seoul. The data obtained were analyzed by Mean, Pearson’s correlation, Stepwise Multiple Regression and Path Analysis. The major findings were as follows: 1) The general tendency of the housewives’wedding behavior and satisfaction was reasonable. 2) According to the background variables(ie: marital form, the existence of job, the recognition degree of her husband’s family’s living standards, the recognition degree of her parents’home’s living standards, the perception of marital transactions), the housewives’wedding behavior was significantly different. 3) According to (1)the background variables(ie: communication frequency in household, self-acceptance, the adequacy of household income, educational level), (2)intermediated variable(ie: articles essential to a marriage), the housewives’wedding satisfaction was significantly different. 4) The indirect variable of the positive influence for housewives’satisfaction of wedding was marital form, the existence of job. the indirect variable of the negative influence for housewives’satisfaction of wedding was the recognition degree of her husband’s family’s living standards, the recognition degree of her parents’home’s living standards, the perception of marital transfactions.

• Korean Journal of Childcare and Education
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• v.14 no.4
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• pp.43-62
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• 2018

Objective: The purpose of this study was to examine the effect of child care teachers' happiness and social support on job performance. Methods: The subjects were 380 teachers employed in child care centers and kindergartens in Gyeonggi Province. Self-report questionnaires were used to investigate teachers' happiness, social support and job performance. The data were analyzed by frequency, percent, Pearson's correlation and stepwise regression with the SPSS program. Results: The results of this study were as follow. First, teachers' job performance was positively associated with teachers' happiness. The highest correlation sub-variable was purpose in life. Next were personal growth, self-acceptance, environmental mastery and autonomy. And the last was positive relationships with others. Teachers' job performance was positively associated with teachers' social support. The highest correlation sub-variable was evaluative support. Next were affective support and material support. And the last was informative support. Second, teachers' happiness and social support affected job performance. Evaluative support, which was a sub-variable of social support, affected job satisfaction. And personal growth, purpose in life, and self-acceptance, which were sub-variables of happiness, affected job satisfaction. Conclusion: This study revealed that teacher's happiness and social support were important factors for teachers job performance.