• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.141-148
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• 2020

We consider estimating the proportion of true null hypotheses in multiple testing problems. A traditional multiple testing rate, family-wise error rate is too conservative and old to control type I error in multiple testing setups; however, false discovery rate (FDR) has received significant attention in many research areas such as GWAS data, FMRI data, and signal processing. Identify differentially expressed genes in microarray studies involves estimating the proportion of true null hypotheses in FDR procedures. However, we need to account for unknown dependence structures among genes in microarray data in order to estimate the proportion of true null hypothesis since the genuine dependence structure of microarray data is unknown. We compare various procedures in simulation data and real microarray data. We consider a hidden Markov model for simulated data with dependency. Cai procedure (2007) and a sliding linear model procedure (2011) have a relatively smaller bias and standard errors, being more proper for estimating the proportion of true null hypotheses in simulated data under various setups. Real data analysis shows that 5 estimation procedures among 9 procedures have almost similar values of the estimated proportion of true null hypotheses in microarray data.

• 대한공업교육학회지
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• v.30 no.1
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• pp.56-67
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• 2005

The purpose of this study was to examine the effects of analytic rubrics on learners' self-directed learning ability in information technology unit assessment. The experiment and control groups were 4 classes of the 2nd grade in B middle school located in Daejeon. The pretest was performed to check the group homogeneity. For the experiment design, the nonequivalent control group design as a type of quasi-experimental design was used. The experiment was composed of 5 sessions. Statistical significance was p < .05 to verify the hypothesis, and SPSS 12.0 for Windows was used for statistical treatment. The results from this study were as follows: (1) The application of analytic rubrics in information technology unit assessment affected learners' self-directed learning ability in a positive way in 4 factor's(openness, self-concept, intrinsic motivation, self-evaluation) but does not affected in 3 factor's(autonomy, creativity, problem solving). (2) The difference in sex was not a statistically significant factor in the application of analytic rubrics in information technology unit assessment. Based on the results of the experiment, two suggestions were made to promote the application of rubrics in technology education assessment. (1) Research and development of many types of rubrics for technology education are needed. (2) Systematic training of rubrics for technology teachers is needed.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.41-61
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• 2001

The minimum negative exponential disparity estimator(MNEDE), introduced by Lindsay(1994), is an excellenet competitor to the minimum Hellinger distance estimator(Beran 1977) as a robust and yet efficient alternative to the maximum likelihood estimator in parametric models. In this paper we define the negative exponential deviance test(NEDT) as an analog of the likelihood ratio test(LRT), and show that the NEDT is asymptotically equivalent to he LRT at the model and under a sequence of contiguous alternatives. We establish that the asymptotic strong breakdown point for a class of minimum disparity estimators, containing the MNEDE, is at least 1/2 in continuous models. This result leads us to anticipate robustness of the NEDT under data contamination, and we demonstrate it empirically. In fact, in the simulation settings considered here the empirical level of the NEDT show more stability than the Hellinger deviance test(Simpson 1989). The NEDT is illustrated through an example data set. We also define a goodness-of-fit statistic to assess adequacy of a specified parametric model, and establish its asymptotic normality under the null hypothesis.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.229-241
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• 1997

We consider discrimination curve and minimum dwell time for Poisson distribution and Poisson-power function distribution. Let the random variable X has Poisson distribution with mean .lambda.. For the hypothesis testing H$\_$0/:.lambda. = t vs. H$\_$1/:.lambda. = d (d$\_$0/ if X.leq.c. Since a critical value c can not be determined to satisfy both types of errors .alpha. and .beta., we considered discrimination curve that gives the maximum d such that it can be discriminated from t for a given .alpha. and .beta.. We also considered an algorithm to compute the minimum dwell time which is needed to discriminate at the given .alpha. and .beta. for the Poisson counts and proved its convergence property. For the Poisson-power function distribution, we reject H$\_$0/ if X.leq..'{c}.. Since a critical value .'{c}. can not be determined to satisfy both .alpha. and .beta., similar to the Poisson case we considered discrimination curve and computation algorithm to find the minimum dwell time for the Poisson-power function distribution. We prosent this algorithm and an example of computation. It is found that the minimum dwell time algorithm fails for the Poisson-power function distribution if the aiming error variance .sigma.$\^$2/$\_$2/ is too large relative to the variance .sigma.$\^$2/$\_$1/ of the Gaussian distribution of intensity. In other words, if .ell. is too small, we can not find the minimum dwell time for a given .alpha. and .beta..

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.867-873
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• 2008

It is a convention to use 5% significance level when a statistical test is employed for clinical data. But when a confidence interval is used for testing equivalence, 90% confidence interval has often been used. When $1-{\alpha}$ confidence interval is used for hypothesis testing, its significance level is often ${\alpha}$. So it makes a confusion that the significance level is 10% if 90% confidence interval is employed for testing equivalence. In this paper I will clarify this issue by reviewing relevant papers and conducting simulation studies. I hope that it will be beneficial to statisticians in pharmaceutical companies, CROs, university hospitals.

• Korean Journal of Veterinary Research
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• v.48 no.3
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• pp.357-361
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• 2008

Although power analysis is of important tool of research, investigators in veterinary medicine are unaware of the concepts of the statistical power. Two types of error occur in classical hypothesis testing and, those errors should be avoided, if possible. Since power is highly dependent on the sample size, whenever declaring non-statistically significant result they should consider the potential for committing a Type II error in their studies, which refers to the probability of falsely stating that two treatments are equivalent despite true difference between them. Also, sample size determination is one of the most important tasks facing the researcher when planning a diagnostic study, and provides valuable information on the characteristics of a test performance. This type of analysis forms the basis for proper interpretation of test results. The aim of this article was to re-evaluate some selected studies on diagnostic test reported in the domestic veterinary publications to determine the power and necessary sample size for inequality testing to ensure the desired power. Power calculations were illustrated using real-life examples of comparison of a new test and a reference test for detecting antibodies of various animal diseases. Factors affecting to the power were also discussed.

• The Journal of Industrial Distribution & Business
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• v.9 no.4
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• pp.7-17
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• 2018

Purpose - This study aims to investigate domestic wine consumption behavior and make future sales strategies and marketing plans. Research design, data, and methodology - To achieve the purpose of the study, the surveys were conducted targeting 350 wine customers in Jeju and Seoul. 331 responses were collected, and out of them, 21 responses were deleted because they lacked the proper information fill in. A descriptive statistical analysis was applied to the remaining 310 responses. The statistical techniques used for carrying out hypothesis-testing are EFA_(exploratory factor analysis), multiple-regression analysis, and moderating effect in SPSS 18.0. Results - The results indicate that fashion oriented, sociality aspiration and rationality seeking lifestyles had significant influence upon internal attributes. However, well-being oriented and having enjoyment oriented lifestyle had no significant influence upon internal attributes. Furthermore, all the types of lifestyles except social aspiration lifestyles had a positive influence upon external attributes, whereas internal or external attributes had positive influence on customer satisfaction. Conclusions - The consumers who experienced wine purchases think wine selection attributes differ before and after experiencing wine drinking, and it shows that the circumstantial variables as purchase situations prove to be important predicted variables in the behavior field of wine consumers. It implies appropriate wine education according to the consuming trend about wine for wine consumers are needed.

• Asia-Pacific Journal of Business
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• v.6 no.1
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• pp.27-43
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• 2015

The objective of the present study is to identify the security factors that influence customer trust towards intention to continue using Internet banking in Malaysia. The participants are individual Internet banking users in Peninsular Malaysia. Data was collected through self-administered questionnaires distributed using the drop-off and pick-up (DOPU) technique to bank branch managers who then passed the questionnaires to their customers. A total of 413 respondents completed the questionnaires. The SPSS statistical analysis software package and Partial Least Squares statistical method were used for data analysis and hypothesis testing. The results show that authentication, confidentiality, data integrity and non-repudiation are significant factors that influence customer trust towards intention to continue using Internet banking. Trust plays a critical role in influencing the intention to continue using Internet banking in Malaysia while perceived privacy does not. An understanding of the factors identified in this study will enable Internet banking providers to effectively and efficiently enhance the security of services and thereby promote continued usage of Internet banking among customers. The findings of this study are thus expected to be of great use to Internet banking providers as improvements in Internet banking security will increase business in the long run.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.112-117
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• 2013

The $\overline{x}$ control chart for the process mean and either the R or s control chart for the process dispersion have been used together to monitor the manufacturing processes. However, it has been pointed out that this procedure is flawed by a fault that makes it difficult to capture the behavior of process condition visually by considering the relationship between the shift in the process mean and the change in the process dispersion because the respective characteristics are monitored by an individual control chart in parallel. Then, the ($\overline{x}$, s) control chart has been proposed to enable the process managers to monitor the changes in the process mean, process dispersion, or both. On the one hand, identifying which process parameters are responsible for out-of-control condition of process is one of the important issues in the process management. It is especially important in the ($\overline{x}$, s) control chart where some parameters are monitored at a single plane. The previous literature has proposed the multiple decision method based on the statistical hypothesis tests to identify the parameters responsible for out-of-control condition. In this paper, we propose how to identify parameters responsible for out-of-control condition using the information criterion. Then, the effectiveness of proposed method is shown through some numerical experiments.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.381-388
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• 2016

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.