• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.333-343
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• 1998

This paper proposes variable stream and sample size(VSSS) group control charts in which both the number of streams selected for sampling and sample size from each of the selected streams are allowed to vary based on the values of the preceding sample statistics. The proposed charts select a small portion of streams and take samples of size n = 1 if both the largest and smallest of sample means fall between the lower and upper threshold limits, and select a large portion of streams and take samples of size n > 1 otherwise. A Markov chain approach is used to derive the formulas for evaluating the performances of the proposed charts. Numerical comparisons are made between the VSSS and fixed stream and sample size(FSSS) group control charts.

• Journal of Veterinary Clinics
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• v.32 no.1
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• pp.73-77
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• 2015

There has been increasing attention on sample size requirements in peer reviewed medical literatures. Accordingly, a statistically-valid sample size determination has been described for a variety of medical situations including diagnostic test accuracy studies. If the sample is too small, the estimate is too inaccurate to be useful. On the other hand, a very large sample size would yield the estimate with more accurate than required but may be costly and inefficient. Choosing the optimal sample size depends on statistical considerations, such as the desired precision, statistical power, confidence level and prevalence of disease, and non-statistical considerations, such as resources, cost and sample availability. In a previous paper (J Vet Clin 2012; 29: 68-77) we briefly described the statistical theory behind sample size calculations and provided practical methods of calculating sample size in different situations for different research purposes. This review describes how to calculate sample sizes when assessing diagnostic test performance such as sensitivity and specificity alone. Also included in this paper are tables and formulae to help researchers for designing diagnostic test studies and calculating sample size in studies evaluating test performance. For complex studies clinicians are encouraged to consult a statistician to help in the design and analysis for an accurate determination of the sample size.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.157-172
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• 1996

The long-existed licence system which has acted as one of the strong barriers to entry in the ocean shipping market in Korea is supposed to repeal in the near future. As a result, competition among the different sizes of firms which are operating under regional shield by means of the licence will be intensified. The main objective of this paper is to estimate the degree of economies of scale and economies of density for various firm sizes. For the successful estimation of economies scale and economies of density, translog cost models are developed and estimated through SURE technique which was suggested by Zeller (1963). The major findings are as follows ; All shipping firms in the sample exhibit economies of scale and density. Even small size shipping firms under licence system, they show substantial economies of scale contrary to the wide-known idea that small-size firms are subject to diseconomies of scale. For the ranked firm sizes according to owned deadweight tons, the degree of economies of scale decreases as the firm sizes are larger and larger. The degree of economies of density moderately declines from the smallest to the firm size of 30-60 thousand deadweight tons and sharply rise thereafter. And the large shipping firms with over half-million deadweight tons exhibit high economies density compared to other sizes of firm. If follows that the larger firms have great advantage in competition if the licence system is abolished.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1211-1219
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• 2013

Recently, the usage of skew-normal distribution, instead of classical normal distribution, is rising up in many statistical theories and applications. In this paper, we deal with saddlepoint approximation for the distribution function of sample mean of skew-normal distribution. Comparing to normal approximation, saddlepoint approximation provides very accurate results in small sample sizes as well as for large or moderate sample sizes. Saddlepoint approximations related to the skew-normal distribution, suggested in this paper, can be used as a approximate approach to the classical method of Gupta and Chen (2001) and Chen et al. (2004) which need very complicate calculations. Through simulation study, we verified the accuracy of the suggested approximation and applied the approximation to Robert's (1966) twin data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1021-1029
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• 2010

In 2009 the former three surveys on small and medium enterprises were combined into one survey to reduce the response burden of enterprises. In this report, we study a sample design for 2009 survey on actual state of small and medium enterprises (SMEs). However, the differences between the manufacturing industries and knowledge-based service industries are so large that we need to consider separate populations in the survey. The total sample size is decided as 10,000 in new survey design for integration. We allocate the sample sizes for the first stratum based on CV and then allocate the sample sizes for the second stratum using root proportional formula. Also we calculate survey weights and propose the formula for the estimators as well as standard errors using weights for each characteristic.

• Physical Therapy Korea
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• v.23 no.2
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• pp.93-99
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• 2016

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

• 전기의세계
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• v.24 no.5
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• pp.107-110
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• 1975

This paper describes computational algorithms and a computer program for optimum determinations of wire conductor sizes of radial or tree-type distibution lones with given constraints. Here, The objective function is defined as the total summation of the volume or weight of respective conductor materials required for buildingup the entire distributing system. Four categories of constraints are applied to the obiective function. That is, on the respective load points constraint is imposed by a specified voltage drop limit, and the respective line elements are capable of carrying the current safely(safety current) and also must maintain the minimum thickness in viewpoint of mechanical strength and legal requirements. And finally, the conductor sizes have to be selected among the standardized size levels of the products. These kinds of optimization problems cannot be solved by the ordinary optimization tediniques such as the Linear Programming Method, SUMT Technique, etc. This paper, therefore, successfully devised the powerful alorithms to solve the problem, using the particular properties or characteristics ingerent to the radial or tree-type distribution system. The computer program developed from the algorithms was applied to several sample systems and shown to be exact and very efficient.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.429-440
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• 2003

Variable sampling rate (VSR) control charts vary the sampling interval and/or the sample size according to value of the control statistic. It is known that $\bar{X}$ charts with VSR scheme lead to large improvements in performance over those with fixed sampling rate (FSR) scheme. In this paper, we studied $\bar{X}$ charts with several VSR schemes, and compared their statistical performance each other.

• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.102-110
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• 1994

We investigate the small-sample behavior of the probability of rejection curves and its performance for a equivalence testing procedure based on confidence intervals which was developed with a motivation from bioequivalence studies. This type of equivalence studies are conducted frequently in pharmaceutical industries to compare the relative bioavailabilty of two formulations of a drug and can be applied various fields where assurance of quality equivalence is needed. From the Monte-Carlo simulation results we suggest proper sample sizes for the equivalence testing procedure.

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.9-20
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• 1990

The purpose of this paper is to propose the modified semiparametric estimators for survival function in the Cox's regression model with randomly censored data based on Tsiatis and Breslow estimators, and present their asymptotic variances estimates. The proposed estimators are compared to Tsiatis, Breslow, and Kaplan-Meier estimators through a small-sample Monte Carlo study. The simulation results show that the proposed estimators are preferred for small sample sizes.