• Journal of Korean Academy of Nursing
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• v.37 no.5
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• pp.715-723
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• 2007

Purpose: The purposes of this study were 1) to compare the contribution of demographic-behavioral variables and psychological variables in explaining the variance of depression, 2) identify the most important predictors of depression for Korean female adolescents. Method: The participants were 840 female adolescents. Data was collected through self-report questionnaires, which were constructed to include demographic-behavioral factors, self-esteem, hostility, hopelessness, and depression. Data was analyzed using the SPSS program. Result: Female adolescents' demographic-behavioral variables explained 17% of the variance in depression, and perceived physical health status, history of physical abuse, smoking, satisfaction of body weight, parental alcohol abuse, parental divorce, and history of suicidal attempt were the significant predictors of depression for female adolescents. Psychological variables explained 50% of the variance in depression, and self-esteem, hostility, and hopelessness were the significant predictors of depression for female adolescents. The significant predictors of depression among female adolescents' demographic-behavioral variables and psychological variables were self-esteem, hostility, hopelessness, perceived physical health status, parental alcohol problem, and history of physical abuse, explaining 52% of the variance in depression. Conclusion: In order to reduce depression in female adolescents, it is necessary to design an intervention program that emphasizes improving self-esteem while reducing hostility and hopelessness.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.3
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• pp.160-166
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• 1989

We propose adaptive algorithms computing the coefficients of spatial domain predictors. The method uses the LMS approach to compute the coefficients of the predictors realized by using the TDL(tapped-delay-line) and the ESC (escalator) structures. The predictors to be presented differ from the conventional ones in the sense that the relevant weights are updated such that the sum of the mean squared values of the forward and the backward prediction errors is minimized. Using the coefficients of such spatial domain predictors yields improved linear predictive spatial spectrums. The algorithms are applied to the problems of estimating incident angles of multiple narrow-band signals received by a linear array of sensors. Simulation results demonstrating the performances of the proposed methods are presented.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.73-84
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• 2020

Existing studies disagree over the core predictors of firm-level financial choices in developing countries. The general practice only validates the traditional capital structure model, which leads to inconsistency and a lack of novelty. This study removed overfitting issues among existing factors and presented the most reliable and advanced capital structure model in Pakistani firms. The panel data include 368 Pakistani companies from 19 non-financial sectors over the period 2004 to 2017. We apply Akaike and Bayesian Information Criteria to remove overfitting issues among inconsistent proxies in the capital structure model. The fixed effects regression is used for basic results and the Generalized Method of Moments is applied to control the endogeneity. Besides the conventional proxies, we report that credit rating, distance from bankruptcy, managerial concentration, and institutional quality are the most advanced capital structure determinants in Pakistan. These predictors remain significant across firm size and growth levels. Also, the findings confirm that new predictors are reliable to define capital structure dynamics and improve the speed of adjustment in overall and sub-sample analysis. The major findings suggest that managers and policymakers should consider these advanced predictors to design their financial settings in firms.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.247-255
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• 1998

In this paper, a new subset selection problem in the Poisson model is considered under the normal predictors. It turns out that the subset model has bigger valiance than that of the Poisson model with random predictors and this has been used to derive new subset selection method similar to Mallows'$C_p$.

• Clinical and Experimental Pediatrics
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• v.62 no.4
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• pp.119-123
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• 2019

Kawasaki disease (KD) is a systemic vasculitis that mainly affects younger children. Intravenous immunoglobulin (IVIG) resistant cases are at increasing risk for coronary artery complications. The strategy on prediction of potential nonresponders and treatment of IVIG-resistant patients is now controversial. In this review the definition and predictors of IVIG-resistant KD and current evidence to guide management are discussed.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.121-135
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• 2001

This paper derives the BLUP in a panel data regression model with two way error components and investigates the performance of various predictors. Through simulation study and real data anaysis some of basic finding is following: the computationally simple FGLS(AM, SA) predictors perform reasonably well when compared with the computationally involved MLE and RMLE predictors.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.169-176
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• 2008

We explore the structure and usefulness of three dimensional CERES plot as a basic tool for dealing with curvature as a function of the new predictors in generalized linear models. If predictors have nonlinear effects and there are nonlinear relationships among the predictors, the partial residual plot is not able to display the correct functional form of the predictors. Unlike this plots, the CERES plot can show the correct form. This is illustrated by simulated data.

• Child Health Nursing Research
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• v.17 no.3
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• pp.181-189
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• 2011

Purpose: This study was done to investigate the predictors of maternal confidence between primipara and multipara mothers. Methods: The participants enrolled in this study were 145 mothers between 2 and 5 days postpartum. Data were collected using a questionnaire and analyzed using descriptive analysis, t-test, $X^2$ test, ANOVA, Pearson correlation coefficients, and stepwise multiple regression. Results: The predictors of maternal confidence among primipara mothers were social support, self-esteem, mode of delivery ($R^2$=.287, p<.001). Whereas, gender of baby, antenatal fetal attachment, and educational status explained maternal confidence among multipara mothers ($R^2$=.270, p<.001). Conclusion: The results indicate that when nurses develop programs to encourage maternal confidence for new mothers, they should take into account the differences between predictors of maternal confidence according to the mothers' experience of birth.

• Journal of the Korean Home Economics Association
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• v.48 no.10
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• pp.89-103
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• 2010

The purpose of this study was to examine the developmental trajectories of adolescents' internalizing problem behaviors. The data came from 3,188 middle school students through their participation in the Korea Youth Panel Survey(KYPS). Adolescents with a high level of internalizing problem behaviors in the first year showed a rapid decline in these behaviors over time, whereas for adolescents with a low level of these behaviors in the first year the decline was slow. The predictors of the developmental trajectories were related to individual variables, such as gender, self-esteem, self-control, stress, self-stigmatization, and academic achievement. The developmental trajectories of adolescents' internalizing problem behaviors were classified into four groups. The predictors of the patterns of developmental trajectories in adolescents' internalizing problem behaviors appeared to be related to individual variables.

• Korean Journal of Adult Nursing
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• v.18 no.4
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• pp.564-572
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• 2006

Purpose: The purpose of this study is to examine predictors of anxiety and PTSD in battered women. Method: The data were collected from 555 women who were stratified samples according to 15,000:1 from a target population in Korea from November 18, 2004 to February 18, 2005. The data was analysed using the SPSS program. Results: Predictors of anxiety were self esteem, stress, state anger, social support, trait anger, negotiation, and psychological violence. These variables explained 55.8% of anxiety. Predictors of PTSD were self esteem, state anger, trait anger, psychological violence, stress, and anger-in. These variables explained 43.2% of PTSD. Conclusion: It is considered that the importance of separating the effects of the different types of violence when taking into account its effects on women's mental health. To promote women's mental health, it is needed to develop self esteem improvement programs, and anger and stress management programs.