• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.965-976
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• 2015

Determining relevant variables for a regression model is important in regression analysis. Recently, a variable selection methods using a penalized likelihood with various penalty functions (e.g. LASSO and SCAD) have been widely studied in simple statistical models such as linear models and generalized linear models. The advantage of these methods is that they select important variables and estimate regression coefficients, simultaneously; therefore, they delete insignificant variables by estimating their coefficients as zero. We study how to select proper variables based on penalized hierarchical likelihood (HL) in semi-parametric frailty models that allow three penalty functions, LASSO, SCAD and HL. For the variable selection we develop a new function in the "frailtyHL" R package. Our methods are illustrated with breast cancer survival data from the Medical Center at Chonnam National University in Korea. We compare the results from three variable-selection methods and discuss advantages and disadvantages.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.921-932
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• 2015

This study analyzed military personnel survivability in regards to offensive operations according to the scientific military training data of a reinforced infantry battalion. Scientific battle training was conducted at the Korea Combat Training Center (KCTC) training facility and utilized scientific military training equipment that included MILES and the main exercise control system. The training audience freely engaged an OPFOR who is an expert at tactics and weapon systems. It provides a statistical analysis of data in regards to state-of-the-art military training because the scientific battle training system saves and utilizes all training zone data for analysis and after action review as well as offers training control during the training period. The methodologies used the Cox PH modeling (which does not require parametric distribution assumptions) and decision tree modeling for survival data such as CART, GUIDE, and CTREE for richer and easier interpretation. The variables that violate the PH assumption were stratified and analyzed. Since the Cox PH model result was not easy to interpret the period of service, additional interpretation was attempted through univariate local regression. CART, GUIDE, and CTREE formed different tree models which allow for various interpretations.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.21-28
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• 2021

The purpose of this study is to analyze the efficiency of the policy direction to see if the government's purpose of relocating public institutions was achieved by analyzing the case of the Korea Housing Finance Corporation, which moved to Busan Metropolitan City in 2014. Based on the Korea Housing Finance Corporation's settlement management disclosure and public institution performance evaluation report from 2009 to 2019, efficiency was compared and analyzed using DEA analysis, work efficiency in management performance evaluation report, and financial ratio. The analysis results are as follows. First, in the case of DEA analysis, the difference in efficiency before and after fat transfer was not noticeable. Second, the efficiency analysis using the performance evaluation report and the financial ratio showed that the efficiency decreased after local relocation. Taken together, in the case of the Korea Housing Finance Corporation, efficiency decreased after local relocation, which can be attributed to sluggish business performance and inefficiency related to financial ratios. However, this study has limitations because it conducted an analysis on the Korea Housing Finance Corporation. To compensate for this, it is necessary to diversify the scope of research targeting all fund-managed quasi-governmental institutions in Korea. Nevertheless, this study is the first study to analyze before and after the relocation of fund-managed quasi-governmental institutions, and is expected to provide significant implications for future policies to be discussed.

• Tuberculosis and Respiratory Diseases
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• v.57 no.2
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• pp.168-179
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• 2004

Background : The statistical analysis is an essential procedure ensuring that the results of researches are based on evidences rather than opinion. The purpose of this study is to evaluate which statistical techniques are used and whether these statistical methods are used appropriately or not in the journal of Tuberculosis and Respiratory Diseases. Materials and Methods : We reviewed 185 articles reported in the journal of Tuberculosis and Respiratory Diseases in 1999. We evaluated the validity of used statistical methods based upon the checklist that was developed on the basis of the guideline for statistical reporting in articles for medical journals by International Committee of Medical Journal Editors. Results : Among 185 articles, original articles and case reports were 110 (59.5%) and 61 (33.0%) respectively. In 112 articles excluding case reports and reviews, statistical techniques were used in 107 articles (95.5%). In 94 articles (83.9%) descriptive and inferential methods were used, while in 13 (11.6%) articles only descriptive methods were used. With the types of inferential statistical techniques, comparison of means was most commonly used (64/94, 68.1%), followed by contingency table (43/94, 45.7%) and correlation or regression (18/94, 19.1%). Among the articles in which descriptive methods were used, 83.2% (89/107) showed inappropriate central tendency and dispersion. In the articles in which inferential methods were used, improper methods were applied in 88.8% (79/89) and the most frequent misuse of statistical methods was inappropriate use of parametric methods (35/89, 39.3%). Only 14 articles (13.1%) were satisfactory in utilization of statistical methodology. Conclusion : Most of the statistical errors found in the journal were misuses of statistical methods related to basic statistics. This study suggests that researchers should be more careful when they describe and apply statistical methods and more extensive statistical refereeing system would be needed.