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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 26, Issue 6 - Dec 2013
Volume 26, Issue 5 - Oct 2013
Volume 26, Issue 4 - Aug 2013
Volume 26, Issue 3 - Jun 2013
Volume 26, Issue 2 - Apr 2013
Volume 26, Issue 1 - Feb 2013
Selecting the target year
Bayesian Multiple Change-Point Estimation for Single Quantum Dot Luminescence Intensity Data
Kima, Jaehee ; Kimb, Hahkjoon ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 569~579
DOI : 10.5351/KJAS.2013.26.4.569
In the field of single-molecule spectroscopy, it is essential to analyze luminescence Intensity changes that result from a single molecule. With the CdSe/ZnS core-shell structured quantum dot photon emission data Bayesian multiple change-point estimation is done with the gamma prior for Poisson parameters and truncated Poisson distribution for the number of change-points.
Confidence Bounds following Adaptive Group Sequential Tests with Repeated Measures in Clinical Trials
Joa, Sook Jung ; Lee, Jae Won ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 581~594
DOI : 10.5351/KJAS.2013.26.4.581
A group sequential design can end a clinical trial early if a confirmed efficacy or a futility of study medication is found during clinical trials. Adaptation can adjust the design of clinical trials based on accumulated data. The key to this methodology is considered to control the overall type 1 error rate while maintaining the integrity of clinical trials. The estimation would be more complex and the sample size calculation will be more difficult if the clinical trials have repeated measurement data. Lee et al. (2002) suggested a repeated observation case by using the independent increments properties of the interim test statistics and investigated the properties of the proposed confidence interval based on the stage-wise ordering. This study extend Lee et al. (2002) to adaptive group sequential design. We suggest test statistics for the adaptation as redesigning the second stage of clinical trials and induce the stage-wise confidence interval of parameter of interests. The simulation will help to confirm the suggested method.
Developing of Exact Tests for Order-Restrictions in Categorical Data
Nam, Jusun ; Kang, Seung-Ho ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 595~610
DOI : 10.5351/KJAS.2013.26.4.595
Testing of order-restricted alternative hypothesis in
contingency tables can be applied to various fields of medicine, sociology, and business administration. Most testing methods have been developed based on a large sample theory. In the case of a small sample size or unbalanced sample size, the Type I error rate of the testing method (based on a large sample theory) is very different from the target point of 5%. In this paper, the exact testing method is introduced in regards to the testing of an order-restricted alternative hypothesis in categorical data (particularly if a small sample size or extreme unbalanced data). Power and exact p-value are calculated, respectively.
A Test of Fit for Inverse Gaussian Distribution Based on the Probability Integration Transformation
Choi, Byungjin ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 611~622
DOI : 10.5351/KJAS.2013.26.4.611
Mudholkar and Tian (2002) proposed an entropy-based test of fit for the inverse Gaussian distribution; however, the test can be applied to only the composite hypothesis of the inverse Gaussian distribution with an unknown location parameter. In this paper, we propose an entropy-based goodness-of-fit test for an inverse Gaussian distribution that can be applied to the composite hypothesis of the inverse Gaussian distribution as well as the simple hypothesis of the inverse Gaussian distribution with a specified location parameter. The proposed test is based on the probability integration transformation. The critical values of the test statistic estimated by simulations are presented in a tabular form. A simulation study is performed to compare the proposed test under some selected alternatives with Mudholkar and Tian (2002)`s test in terms of power. The results show that the proposed test has better power than the previous entropy-based test.
The Spatial Correlation of Mode Choice Behavior based on Smart Card Transit Data in Seoul
Park, Man Sik ; Eom, JinKi ; Heo, Tae-Young ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 623~634
DOI : 10.5351/KJAS.2013.26.4.623
In this study, we provide empirical evidence of whether a spatial correlation among mode choices at the TAZ(Traffic Analysis Zone) level exists based on transit smart card data observed in Seoul, Korea. The results show that the areas with a higher probability that passengers choose to take a bus are clustered and that those regions have fewer metro stations than bus stations. We also found that the spatial correlation turned out to be statistically meaningful and provided an opportunity for the potential use of the spatial correlation in modeling mode choices. A reliable spatial interaction would constitute valuable information for transportation agencies in terms of their route planning and scheduling based on the transit smart card data.
Multiple Imputation Reducing Outlier Effect using Weight Adjustment Methods
Kim, Jin-Young ; Shin, Key-Il ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 635~647
DOI : 10.5351/KJAS.2013.26.4.635
Imputation is a commonly used method to handle missing survey data. The performance of the imputation method is influenced by various factors, especially an outlier. The removal of the outlier in a data set is a simple and effective approach to reduce the effect of an outlier. In this paper in order to improve the precision of multiple imputation, we study a imputation method which reduces the effect of outlier using various weight adjustment methods that include the removal of an outlier method. The regression method in PROC/MI in SAS is used for multiple imputation and the obtained final adjusted weight is used as a weight variable to obtain the imputed values. Simulation studies compared the performance of various weight adjustment methods and Monthly Labor Statistic data is used for real data analysis.
Analysis of the Korean Baseball League using a Markov Chain Model
Moon, Hyung Woo ; Woo, Yong Tae ; Shin, Yang Woo ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 649~659
DOI : 10.5351/KJAS.2013.26.4.649
We use a Markov chain model to analyze the Korean Baseball League. We derive the distributions of the number of runs scored and the number of batters that complete their turn at bat in a baseball game using the time inhomogeneous Markov chain. The model is tested with real data produced from the 2011 Korean Baseball League.
Investigating the Behavior of College Students in Class Registration using Social Network Analysis
Lim, Sung-Min ; Kim, Jinheum ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 661~674
DOI : 10.5351/KJAS.2013.26.4.661
We investigate the class registration behavior of college students with data collected from the spring semester of 2012. The network originally consists of a 2-mode network between a student and class subjects. We first transform the 2-mode network into 1-mode network of students. We also subdivide it into a smaller network such as components and communities to understand the detailed behavior of students in class registration. Finally, the relationship between GPA and the centrality measures, gender, and grade of students is analyzed using a multiple regression analysis.
Some Statistical Considerations on 2×k Crossover Designs for Bioequivalence Trial
Noh, So-Young ; Park, Sang-Gue ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 675~686
DOI : 10.5351/KJAS.2013.26.4.675
The Korea Food and Drug Administration(KFDA) recommends the use of a
crossover design to assess the bioequivalence of generic drugs. However, a standard
crossover design for bioequivalence trials is often considered problematic due to ethical and economic issues as highly variable drugs are usually required by large numbers of subjects when designing the trial. To overcome this problem a
crossover design has been a recommended option as per US regulations; in addition, a
crossover design has also recently drawn special attention as an efficient alternative. The current KFDA regulation requires an ANOVA table for every bioequivalence study; however, ANOVA tables of
crossover designs have never been published in the literature. This study shows the derivation of tables of analysis of variance for a
cross-over design and a
cross-over design. We also suggest a sample size formulas for
crossover designs to provide information on the selection of efficient designs for highly variable drugs.
An Outlier Detection Method in Penalized Spline Regression Models
Seo, Han Son ; Song, Ji Eun ; Yoon, Min ;
Korean Journal of Applied Statistics, volume 26, issue 4, 2013, Pages 687~696
DOI : 10.5351/KJAS.2013.26.4.687
The detection and the examination of outliers are important parts of data analysis because some outliers in the data may have a detrimental effect on statistical analysis. Outlier detection methods have been discussed by many authors. In this article, we propose to apply Hadi and Simonoff`s (1993) method to penalized spline a regression model to detect multiple outliers. Simulated data sets and real data sets are used to illustrate and compare the proposed procedure to a penalized spline regression and a robust penalized spline regression.