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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Korean Journal of Applied Statistics
Journal Basic Information
Journal DOI :
The Korean Statistical Society
Editor in Chief :
Volume & Issues
Volume 29, Issue 5 - Aug 2016
Volume 29, Issue 4 - Jun 2016
Volume 29, Issue 3 - Apr 2016
Volume 29, Issue 2 - Feb 2016
Volume 29, Issue 1 - Feb 2016
Selecting the target year
Assessing bioequivalence for highly variable drugs based on 3×3 crossover designs
Park, Ji-Ae ; Park, Sang-Gue ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 279~289
DOI : 10.5351/KJAS.2016.29.2.279
Bioequivalence trials based on higher order crossover designs have recently been conducted for highly variable drugs since the Ministry of Korea Food and Drug Safety (MFDS) added new regulations in 2013 to widen bioequivalence limits for highly variable drugs. However, a statistical discussion of higher order crossover designs have not been discussed yet. This research proposes the statistical inference of bioequivalence based on
crossover design and discusses it with the MFDS regulations. An illustrated example is also given.
Estimable functions of mixed models
Choi, Jaesung ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 291~299
DOI : 10.5351/KJAS.2016.29.2.291
This paper discusses how to establish estimable functions when there are fixed and random effects in design models. It proves that estimable functions of mixed models are not related to random effects. A fitting constants method is used to obtain sums of squares due to random effects and Hartley's synthesis is used to calculate coefficients of variance components. To test about the fixed effects the degrees of freedom associated with divisor are determined by means of the Satterthwaite approximation.
On the asymptotic correlationship for some process capability indices Ĉ
under bivariate normal distribution
Cho, Joong-Jae ; Park, Hyo-Il ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 301~308
DOI : 10.5351/KJAS.2016.29.2.301
The process capability index is used to determine whether a production process is capable of producing items within a specified tolerance. Some process capability indices
have been of particular interest as useful management tools for tracking process performance. Most evaluations on process capability indices focus on statistical estimation and test of hypothesis. It is necessary to investigate their asymptotic correlationship among basic estimators
of process capability indices
. In this paper, we study their asymptotic correlationship for three process capability indices
under bivariate normal distribution BN(
). With some nonnormal processes, the asymptotic correlation coefficient of any two respective process capability index estimators could be established.
Parameter estimation for the imbalanced credit scoring data using AUC maximization
Hong, C.S. ; Won, C.H. ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 309~319
DOI : 10.5351/KJAS.2016.29.2.309
For binary classification models, we consider a risk score that is a function of linear scores and estimate the coefficients of the linear scores. There are two estimation methods: one is to obtain MLEs using logistic models and the other is to estimate by maximizing AUC. AUC approach estimates are better than MLEs when using logistic models under a general situation which does not support logistic assumptions. This paper considers imbalanced data that contains a smaller number of observations in the default class than those in the non-default for credit assessment models; consequently, the AUC approach is applied to imbalanced data. Various logit link functions are used as a link function to generate imbalanced data. It is found that predicted coefficients obtained by the AUC approach are equivalent to (or better) than those from logistic models for low default probability - imbalanced data.
Run expectancy and win expectancy in the Korea Baseball Organization (KBO) League
Moon, Hyung Woo ; Woo, Yong Tae ; Shin, Yang Woo ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 321~330
DOI : 10.5351/KJAS.2016.29.2.321
Run expectancy (RE) is the mean number of runs scored from a specific base runner/outs situation of an inning to the end of the inning. Win expectancy (WE) is the probability that a particular team will win the game at a specific game state such as half-inning, score difference, outs, and/or runners on base. In this paper, we derive RE and WE for the Korea Baseball Organization (KBO) League based on six-year data from 2007 to 2012 using a Markov chain model.
Bayesian structural equation modeling for analysis of climate effect on whole crop barley yield
Kim, Moonju ; Jeon, Minhee ; Sung, Kyung-Il ; Kim, Young-Ju ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 331~344
DOI : 10.5351/KJAS.2016.29.2.331
Whole Crop Barley (WCB) is a representative self-sufficient winter annual forage crop, along with Italian Ryegrass (IRG), in Korea. In this study, we examined the path relationship between WCB yield and climate factors such as temperature, precipitation, and sunshine duration using a structural equation model. A Bayesian approach was considered to overcome the limitations of the small WCB sample size. As prior distribution of parameters in Bayesian method, standard normal distribution, the posterior result of structural equation model for WCB, and the posterior result of structural equation model for IRG (which is the most popular winter crop) were used. Also, Heywood case correction in prior distribution was considered to obtain the posterior distribution of parameters; in addition, the best prior to fit the characteristics of winter crops was identified. In our analysis, we found that the best prior was set by using the results of a structural equation model to IRG with Heywood case correction. This result can provide an alternative for research on forage crops that have hard to collect sample data.
Analyzing landslide data using Cauchy cluster process
Lee, Kise ; Kim, Jeonghwan ; Park, No-wook ; Lee, Woojoo ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 345~354
DOI : 10.5351/KJAS.2016.29.2.345
Inhomogeneous Poisson process models are widely applied to landslide data to understand how environmental variables systematically influence the risk of landslides. However, those models cannot successfully explain the clustering phenomenon of landslide locations. In order to overcome this limitation, we propose to use a Cauchy cluster process model and show how it improves the goodness of fit to the landslide data in terms of K-function. In addition, a numerical study is performed to select the optimal estimation method for the Cauchy cluster process.
Firework plot as a graphical exploratory data analysis tool for evaluating the impact of outliers in skewness and kurtosis of univariate data
Moon, Sungho ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 355~368
DOI : 10.5351/KJAS.2016.29.2.355
Outliers and influential data points distort many data analysis measures. Jang and Anderson-Cook (2014) proposed a graphical method called a rework plot for exploratory analysis purpose so that there could be a possible visualization of the trace of the impact of the possible outlying and/or influential data points on the univariate/bivariate data analysis and regression. They developed 3-D plot as well as pairwise plot for the appropriate measures of interest. This paper further extends their approach to identify its strength. We can use rework plots as a graphical exploratory data analysis tool to evaluate the impact of outliers in skewness and kurtosis of univariate data.
A study on target Sigma Level at R&D stage and robust limits for design margins
Ko, Seoung-gon ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 369~379
DOI : 10.5351/KJAS.2016.29.2.369
The Sigma Level, proposed by Motorola Inc., is one of the many Process Capability Index (PCI)'s that have been presented since the 1970's. It is used to evaluate process capability and unlike other PCI's, it has an advantage in that it uses population probability distribution. However, it is originally designed for mass production and is inadequate to evaluate prototypes or early products in the R&D stages. For use in such cases, we propose an R&D target Sigma Level, derived by considering 1.5 sigma shifts in traditional sigma level from a statistical point of view. We also explain the way to find robust limits for design tolerance because the sigma level or defect probability is useful to establish economical tolerance limits at the R&D stage and mass production.
Visualization in the assessment of construct validity
Noh, Hohsuk ; Song, Ji Na ; Cho, Hyeyoon ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 381~388
DOI : 10.5351/KJAS.2016.29.2.381
It is common to quantify the concept of interest in the social and human sciences to test a research hypothesis. In such a case, it is strongly recommended to investigate if the procedure is appropriately designed and implemented according the research purpose since the quantification procedure highly affects the result of statistical analysis. In this work, we propose a visualization tool which enables us to check the construct validity of a measurement tool (such a questionnaire) in a concise and convenient way based on a penalized factor analysis model. We illustrate our method with numerical simulation and real data analysis.
Financial performance analysis of guaranteed firms using propensity scores
Nam, Joo-Ha ; Kim, Jung-Ryol ; Noh, Maengseok ;
Korean Journal of Applied Statistics, volume 29, issue 2, 2016, Pages 389~398
DOI : 10.5351/KJAS.2016.29.2.389
In this paper, we examine the financial performance of credit guarantee programs. We compared financial performance of guaranteed firms of KODIT and non-guaranteed firms. The of covariate adjusted propensity score method is used because a selection bias problem could occur if t-test or regression analysis were used. The results show that a credit guarantee program enhances the financial performance of beneficiary firms.