• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1481-1489
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• 2014

For predicting yearly total attendances in Korean probaseball games, ARIMA models have been widely adopted so far. In this paper, we discuss two other ways of ARIMAX and growth curves with an exogenous variable to predict the attendances. By using the exogenous variable, it turns out that the prediction has been improved compared to ARIMA. It is concluded that various statistical methods must be considered for better prediction, and its results can be applied to predict the attendances of other pro sports.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5655-5661
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• 2015

Purpose: To assess the role of two adjuvant chemotherapy regimens, anthracycline-based and CMF on disease free survival and overall survival breast cancer patients by meta-analysis approach in Eastern Mediterranean and Asian countries to determine which is more effective and evaluate the appropriateness and efficiency of two different proposed statistical models. Materials and Methods: Survival curves were digitized and the survival proportions and times were extracted and modeled to appropriate covariates by two multivariate mixed effects models. Studies which reported disease free survival and overall survival curves for anthracycline-based or CMF as adjuvant chemotherapy that were published in English in the Eastern Mediterranean region and Asia were included in this systematic review. The two transformations of survival probabilities (Ln (-Ln(S)) and Ln(S/ (1-S))) as dependent variables were modeled by a multivariate mixed model to same covariates in order to have precise estimations with high power and appropriate interpretation of covariate effects. The analysis was carried out with SAS Proc MIXED and STATA software. Results: A total of 32 studies from the published literature were analysed, covering 4,092 patients who received anthracycline-based and 2,501 treated with CMF for the disease free survival and in order to analyze the overall survival, 13 studies reported the overall survival curves in which 2,050 cases were treated with anthracycline-based and 1,282 with CMF regimens. Conclusions: The findings illustrated that the model with dependent variable Ln (-Ln(S)) had more precise estimations of the covariate effects and showed significant difference between the effects of two adjuvant chemotherapy regimens. Anthracycline-based treatment gave better disease free survival and overall survival. As an IPD meta-analysis in the Italy the results of Angelo et al in 2011 also confirmed that anthracycline-based regimens were more effective for survival of breast cancer patients. The findings of Zare et al 2012 on disease free survival curves in Asia also provided similar evidence.

• Journal of the Korean Chemical Society
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• v.46 no.4
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• pp.377-384
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• 2002

In this study, the effect of cooperative computer-assisted instruction upon students' conceptual under-standing,application ability, and learning motivation were investigated by a previous achievement level. The treatment and the control groups (2 classes) were selected from a middle school in Seoul, and taught about the motion of molecule for 5 class periods. Prior to the instructions, a learning motivation test was administered and used as covariate. The scores of a previous achievement test were also used as covariate. The scores of the mid-term science examination were used as blocking variable. After the instructions, the conceptions test, the application test, and the learning motivation test were administered. Two-way ANCOVA results revealed that there were no significant differences in the scores of the con-ceptions test and the application test. However, the scores of the treatment group were found to be significantly higher than those of the control group in the learning motivation test.

• International Journal of Human Ecology
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• v.8 no.1
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• pp.9-18
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• 2007

This study focuses on the relationship between ethnic identity of Asian-Americans and their appreciation of their ethnic body features, based on reference group theory. A convenience sample of 60 male and 52 female students from various Asian ethnicities attending a mid-western university was used for the study. A 2 (gender) by 2 (ethnic identification) by 2 (socializing group) analysis of covariance (ANCOVA) on body image satisfaction as dependent variable and Body Mass Index score as a covariate was conducted. A significant main effect of ethnic identification was found, which indicates the more respondents identified with their ethnic group, the more likely they were to be satisfied with their appearance. The social group affiliation main effect was not significant. The impact of ethnic identification was significant only for those respondents who socialize more with Americans than with Asians. The results support the idea that one's ethnic group functions as a reference group, which influences body image appraisals.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.697-707
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• 2017

In this paper, we propose a modified GARCH(p, q)-X model which is obtained by adding the exogenous variables to the modified GARCH(p, q) process. Some limiting properties are shown under various stationary and nonstationary exogenous processes which are generated by another process independent of the noise process. The proposed model extends the GARCH(1, 1)-X model studied by Han (2015) to various GARCH(p, q)-type models such as GJR GARCH, asymptotic power GARCH and VGARCH combined with exogenous process. In comparison with GARCH(1, 1)-X, we expect that many stylized facts including long memory property of the financial time series can be explained effectively by modified GARCH(p, q) model combined with proper additional covariate.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.265-269
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• 2005

Cox's proportional hazards model (PHM) has been widely applied in the analysis of lifetime data, and it can be characterized by the baseline hazard function and covariates influencing systems' lifetime, where the covariates describe operating environments (e.g. temperature, pressure, humidity). In this article, we consider the constant baseline hazard function and a discrete random variable of a covariate. The estimation procedure is developed in a parametric framework when there are not only complete data but also incomplete one. The Expectation-Maximization (EM) algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

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

• Journal of Korean Critical Care Nursing
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• v.13 no.3
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• pp.41-50
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• 2020

Purpose : This descriptive research study aimed to identify the factors influencing nursing students' empathy and gender role identity and their effect on communication competence. Methods : Participants were 183 senior nursing students who had completed a clinical practice and simulation-based practical training course. Using the IBM SPSS/WIN 21.0 program, general characteristics were analyzed using descriptive statistics, independent variables were compared with t-tests and 𝑥² tests, and influencing factors on each variable and communication underwent multiple linear regression analysis. Results : Communication competence showed significant correlations with empathy (r=.40, p<.001), gender role identity (r=.53, p<.001), major satisfaction (r=.18, p=.013), and peer relationships (r=.24, p<.001). When gender was entered as a covariate, empathy (t=4.41, p<.001) and gender role identity (t=6.97, p<.001) were identified as predictors affecting communication competence with 36% explanation power (R²=.36, p<.001). Conclusion : The findings of this study suggest that course subjects considering the gender identities of students should be developed through various programs to establish students' identity as nurses and improve their empathy and communication.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.543-553
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• 2016

The validity of statistical inference depends on proper randomization methods. However, even with proper randomization, we can have imbalanced with respect to important characteristics. In this paper, we introduce a method based on ranked auxiliary variables for treatment allocation in crossover designs using Latin squares models. We evaluate the improvement of the efficiency in treatment comparisons using the proposed method. Our simulation study reveals that our proposed method provides a more powerful test compared to simple randomization with the same sample size. The proposed method is illustrated by conducting an experiment to compare two different concentrations of titanium dioxide nanofiber (TDNF) on rats for the purpose of comparing weight gain.