• Journal of Korean Society for Quality Management
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• v.28 no.2
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• pp.17-38
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• 2000

In application, sample size determination is one of the important problems in designing an experiment. A large amount of literature has been published on the problem of determining sample size and power for various statistical models. In practice, however, it is not easy to calculate sample size and/or power because the formula and other results derived from statistical model are scattered in various textbooks and journal articles. This paper describes some previously published theories that have practical relevance for sample size and power determination in various statistical problems, including life-testing problems with censored cases and introduces a statistical package which calculates sample size and power according to the results described. The screens and numerical results made by the package are demonstrated.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.114-121
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• 2007

Power and sample size estimation is one of the crucially important steps in planning a genetic association study to achieve the ultimate goal, identifying candidate genes for disease susceptibility, by designing the study in such a way as to maximize the success possibility and minimize the cost. Here we review the optimal two-stage genotyping designs for genomewide association studies recently investigated by Wang et al(2006). We review two mathematical frameworks most commonly used to compute power in genetic association studies prior to the main study: Monte-Carlo and non-central chi-square estimates. Statistical powers are computed by these two approaches for case-control genotypic tests under one-stage direct association study design. Then we discuss how the linkage-disequilibrium strength affects power and sample size, and how to use empirically-derived distributions of important parameters for power calculations. We provide useful information on publicly available softwares developed to compute power and sample size for various study designs.

• Journal of Power Electronics
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• v.12 no.1
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• pp.164-171
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• 2012

Variable step size maximum power point trackers (MPPTs) are widely used in photovoltaic (PV) systems to extract the peak array power which depends on solar irradiation and array temperature. One essential factor which judges system dynamics and steady state performances is the scaling factor (N), which is used to update the controlling equation in the tracking algorithm to determine a new duty cycle. This paper proposes a novel stability study of variable step size incremental resistance maximum power point tracking (INR MPPT). The main contribution of this analysis appears when developing the overall small signal model of the PV system. Therefore, by using linear control theory, the boundary value of the scaling factor can be determined. The theoretical analysis and the design principle of the proposed stability analysis have been validated using MATLAB simulations, and experimentally using a fixed point digital signal processor (TMS320F2808).

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.53-61
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• 2012

There are cases when the sample size is determined based not only on the significance level but also on on the power or type II error. In this paper, we implemented the sample size and the power calculation when both the significance level and power for testing means in normal distributions and proportions in binomial distributions. The implementation is available on a web site. Alternately, we also calculate the power for a given effect size, type I error probability and sample size.

• 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.

• Journal of Animal Science and Technology
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• v.55 no.2
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• pp.103-107
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• 2013

A crucial first step in the planning of any scientific experiment is to evaluate an appropriate sample size to permit sufficient statistical power to detect the desired effect. In this study, we investigated the optimal sample size of quantitative trait locus (QTL) linkage analysis for simple random sibship samples in pedigreed chicken populations, under the variance component framework implemented in the genetic power calculator program. Using the program, we could compute the statistical power required to achieve given sample sizes in variance component linkage analysis in random sibship data. For simplicity, an additive model was taken into account. Power calculations were performed to relate sample size to heritability attributable to a QTL. Under the various assumptions, comparative power curves indicated that the power to detect QTL with the variance component method is highly affected by a function of the effect size of QTL. Hence, more power can be achievable for QTL with a larger effect. In addition, a marked improvement in power could be obtained by increasing the sibship size. Thus, the use of chickens is advantageous regarding the sampling unit issue, since desirable sibship size can be easily obtained compared with other domestic species.

• Women's Health Nursing
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• v.4 no.3
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• pp.375-387
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• 1998

In clinical trials of nursing research, the sample size determination is one of the most important factor. Although sample size must be considered at the design stage, it has been disregarded in most clinical trials. The power analysis is usually performed before study begins to compute sample size and the power can also be calculated at the end of study in order to justify study result. The power analysis is essential especially when the clinical trials can not show significant differences. In this paper, we review the statistical methods for power analysis and sample size formulae in nursing research. Sample size formulae and the corresponding examples are discussed according to the six types of studies ; mean for one sample, proportion for one sample, means in two samples, proportions in two samples, correlation coefficient and ANOVA.

• Journal of Biosystems Engineering
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• v.6 no.1
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• pp.60-72
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• 1981

This study was carried out to find out the effects of the sheaf size of paddy harvested by the binders on the threshing performance, load characteristics and power requirement of an auto-feed thresher. The results of the study are summarized as follows: 1. The seperating performance of the thresher appeared to be satisfactory for all the sheaf sizes although the amount of rubbishes and empty grains slightly increased with the sheaf size of paddy. 2. There was no significant difference in grain output quality of the thresher among the three sheaf sizes. However, the amount of grains left unthreshed increased with the sheaf size. In the case of the largest sheaf size with the feed rate of 780kg/h, it exceeded the limit set by the national inspection regulations. 3. The position of the feed-chain rail gave a significant effect on the power requirement of the thresher. At the feed rate of 780kg/h, the net power required to convey sheafs through the feed chain was in the range of 0.37 to 0.50 PS for the middle and lowest position of feed-chain rail, and there was no significant difference among the sheaf sizes. At the highest position, however, it appeared that the smallest sheaf required more power than the others. The net power requirements at this position were 1.03, 0.59. 0.65 PS for the smallest, medium and largest sheafs respectively. 4. The torques of both the thresher and the engine shaft increased with the feed rate and were not affected by the sheaf size for the lower two feed rates of 520 and 780kg/h. At the highest feed rate of 1,040 kg/h, however, they were affected by the sheaf size. In this case, the medium sheaf size gave lower values than the others. 5. The variations in the thresher and the engine torque increased with the feed rate and were not affected by the sheaf size for the feed rate of 520kg/h. At the feed rate of 780kg/h, however, they increased with sheaf size. And at the feed rate of 1,040 kg/h, the torque variations increased greatly for all the sheaf sizes due to an over-load operating condition. 6. It appeared that the average and maximum power requirements of the thresher increased with the feed rate. But, there was no significant difference in power requirement among the sheaf sizes for the lower two feed rates. 7. The threshing efficiency of the thresher was in the range of 214-249 kg/ps.h with the feed rates of 520 and 780 kg/h, and it was not affected by both the sheaf size and the feed rate. At the feed rate of 1,040 kg/h, however, it decreased to as low as 171-174 kg/ps.h because of a sudden increase in power requirement. 8. The average power requirements of the engine were slightly higher than those of the thresher due to the slippage of flat belt between the thresher and engine. It appeared that power transmission from the engine to the thresher was maintained properly since slippages were moderately low with the range of 2.78 to 6.51% throughout the tests. 9. The specific fuel consumption of the engine (diesel 8PS) decreased as the feed rate increased. However, there was no significant reduction in specific fuel consumption as the feed rate increased above 780 kg/h.

• The Journal of the Korean dental association
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• v.52 no.9
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• pp.558-569
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• 2014

Sample size determination is critical, but not easy to do. Sample size defined as the number of observations in a sample to be studied should be big enough to have a high likelihood of detecting a true difference between groups. Practical procedure for determining sample size, using $G^*$power and previous dental articles, was shown in this study. Examples involving independent t-test, paired t-test, one-way analysis of variance(ANOVA), and one-way repeated-measures(RM) ANOVA were used. The purpose of this study is to enable researchers with non-statistical backgrounds to use in practice freely available statistical software G*power to determine sample size and power.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.167-169
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• 2021

In this study, monodispersive silica nanoparticles with double mesoporous shells were synthesized, and the pore size of synthetic mesoporous silica nanoparticles was controlled. Cetyltrimethylammonium chloride (CTAC), N, N-dimethylbenzene, and decane were used as soft template and induced to form outer mesoporous shell. The resultant double mesoporous silica nanoparticles were consisted of two layers of shells having different pore sizes, and it has been confirmed that outer shells with larger pores (Mean pore size > 2.5 nm) are formed directly on the surface of the smaller pore sized shell (Mean pore size < 2.5 nm). It was confirmed that the regulation of the molar ratio of pore expansion agents plays a key role in determining the pore size of double mesoporous shells.