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

• Journal of Pharmaceutical Investigation
• /
• v.39 no.3
• /
• pp.217-219
• /
• 2009

There are several approaches to calculate a sample size for bioequivalence test. Among these approaches, sample sizes determination based on Schuirmann's two one-sided tests procedures has been used most popularly in case of 2${\times}$2 bioequivalence study. Here we proposed simple sample size table for conventional 2${\times}$2 bioequivalence test based on Schuirmann's two one-sided tests in accordance with Korean Guidelines for Bioequivalence Test. This table will allow researchers with a little statistical background to calculate the sample size for bioequivalence with easy process.

• Journal of Korean Society for Quality Management
• /
• v.32 no.4
• /
• pp.252-264
• /
• 2004

Variable sampling Interval (VSI) control charts vary the sampling interval according to value of the control statistic while the sample size is fixed. It is known that control charts with 2-state VSI scheme, which uses only two sampling intervals, give good statistical properties. Variable sample size (VSS) control charts vary the sample size according to value of the control statistic while the sampling interval is fixed. In the VSS scheme no optimal results are known for the number of sample sizes. It is also known that the variable sampling rate (VSR) $\bar{X}$ control chart with 2-state VSS and 2-state VSI scheme leads to large improvements In performance over the fixed sampling rate (FSR) $\bar{X}$ chart, but the optimal number of states for sample size Is not known. In this paper, the VSR Χ charts with multi-state VSS and 2-state VSI scheme are designed and compared to 2-state VSS and 2-state VSI scheme. The multi-state VSS scheme is considered to, achieve an additional improvement by switching from the 2-state VSS scheme. On the other hand, the multi-state VSI scheme is not considered because the 2-state scheme is known to be optimal. The 3-state VSS scheme improves substantially the sensitivity of the $\bar{X}$ chart especially for small and moderate mean shifts.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.34 no.1
• /
• pp.29-37
• /
• 2009

This paper proposes a curtailed-sequential probability ratio test (SPRT) control chart. For using the conventional SPRT control chart, the number of items inspected in a sampling point should have no restriction since items in a sampling point are inspected one by one until an SPRT Is terminated. The number of observations taken in a sampling point, however, has an upper bound since sampling and testing of an item is time-consuming or expensive. When the sample size reaches the upper bound without evidence of an in-control or out-of-control state of a process, the proposed chart makes a decision using the sample mean of all observations taken in a sampling point. The properties of the Proposed chart are obtained by a Markov chain approach and the performance of the chart is compared with fixed sample size (FSS) and variable sample size (VSS) control charts. A comparative study shows that the proposed chart performs better than VSS control charts as well as conventional FSS control charts.

• The Korean Journal of Applied Statistics
• /
• v.24 no.2
• /
• pp.393-400
• /
• 2011

In a large scale survey, cluster sampling design in which a set of observation units called clusters are selected is often used to satisfy practical restrictions on time and cost. Especially, a two stage cluster sampling design is preferred when a strong intra-class correlation exists among observation units. The sample Primary Sampling Unit(PSU) and Secondary Sampling Unit(SSU) size for a two stage cluster sample is determined by the survey cost and precision of the estimator calculated. For this study, we derive the optimal sample PSU and SSU size when the population SSU size across the PSU are di erent by extending the result obtained under the assumption that all PSU have the same number of SSU. The results on the sample size are then applied to the $4^{th}$ Korea Hospital Discharge results and is compared to the conventional method. We also propose the optimal sample SSU (discharged patients) size for the $7^{th}$ Korea Hospital Discharge Survey.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.6
• /
• pp.1349-1357
• /
• 2013

In clinical research, sample size determination is one of the most important things. There are parametric method using t-test and non-parametric method suggested by Kim and Kim (2007) based on Wilcoxon's rank sum test for determining sample size in non-inferiority trials. In this paper, we propose sample size calculation method based on placements method suggested by Orban and Wolfe (1982) and using the power calculated by Kim (1994) in non-inferiority trials. We also compare proposed sample size with that using Kim and Kim (2007)'s formula and that of t-test for parametric methods. As the result, sample size calculated by proposed method based on placements is the smallest. Therefore, proposed method based on placements is better than parametric methods in case that it's hard to assume specific distribution function for population and also more efficient in terms of time and cost than method based on Wilcoxon's rank sum test.

• Korean Journal of Veterinary Research
• /
• v.50 no.1
• /
• pp.43-48
• /
• 2010

Animal disease surveillance system, defined as the continuous investigation of a given population to detect the occurrence of disease or infection for control purposes, has been key roles to assess the health status of an animal population and, more recently, in international trade of animal and animal products with regard to risk assessment. Especially, for a system aiming to determine whether or not a disease is present in a population sensitivity of the system should be maintained high enough not to miss an infected animal. Therefore, when planning the implementation of surveillance system a number of factors that affecting surveillance sensitivity should be taken into account. Of these parameters sample size is of important, and different approaches are used to calculate sample size, usually depending on the objective of surveillance systems. The purpose of this study was to evaluate the sensitivity of the current national serological surveillance programs for four selected bovine diseases assuming a specified sampling plan, to examine factors affecting the probability of detection, and to provide sample sizes required for achieving surveillance goal of detecting at least an infection in a given population. Our results showed that, for example, detecting low level of prevalence (0.2% for bovine tuberculosis) requires selection of all animals per typical Korean cattle farm (n = 17), and thus risk-based target surveillance for high risk groups can be an alternative strategy to increase sensitivity while not increasing overall sampling efforts. The minimum sample size required for detecting at least one positive animal was sharply increased as the disease prevalence is low. More importantly, high reliability of prevalence estimation was expected with increased sampling fraction even when zero-infected animal was identified. The effect of sample size is also discussed in terms of the maximum prevalence when zero-infected animals were identified and on the probability of failure to detect an infection. We suggest that for many serological surveillance systems, diagnostic performance of the testing method, sample size, prevalence, population size, and statistical confidence need to be considered to correctly interpret results of the system.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.2
• /
• pp.78-88
• /
• 2009

In many face recognition problems, the number of available images is limited compared to the dimension of the input space which is usually equal to the number of pixels. This problem is called as the 'small sample size' problem and regularization methods are typically used to solve this problem in feature extraction methods such as LDA. By using regularization methods, the modified within class matrix becomes nonsingu1ar and LDA can be performed in its original form. However, in the process of adding a scaled version of the identity matrix to the original within scatter matrix, the scale factor should be set heuristically and the performance of the recognition system depends on highly the value of the scalar factor. By using the proposed resampling method, we can generate a set of images similar to but slightly different from the original image. With the increased number of images, the small sample size problem is alleviated and the classification performance increases. Unlike regularization method, the resampling method does not suffer from the heuristic setting of the parameter producing better performance.

• Applied Chemistry for Engineering
• /
• v.9 no.3
• /
• pp.430-434
• /
• 1998

Preparative HPLC (High-Performance Liquid Chromatography) is mainly used for separating useful component from biological samples. By reversed-phase HPLC packed with preparative packings ($15{\mu}m$), the adsorption characteristics with sample size were investigated. Sample was 5'-GMP, a flavor enhancer, and the composition of mobile phase was 20mM $KH_2PO_4$ solution:methanol (97:3 vol.%). From the experimental results, the effect of sample size on retention factor was negligible, but the peak was asymmetrical above $1{\mu}g$ of sample. In addition, the increase in sample size deteriorated the number of theoretical plates, and at small concentration, the number of theoretical plates was less because of large peak width. In the experimental condition, the adsorption isotherm of 5'-GMP was relatively well represented by Freundlich equation.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.30 no.2
• /
• pp.204-209
• /
• 2001

The effects of size distribution of oil particles on the emulsion stability of mayonnaise were studied as follows; The stability of mayonnaise has concerned closely with the viscosity and the size distribution of oil particles. Mostly, if the viscosity was increased, the stability was improved, and the distribution of oil particles was uniform and the less the variation, the more the stability. 75% of oil concentration of sample showed the highest viscosity, also the size of sample was the most uniform, compared to other concentration. Mayonnaise prepared with whole egg was unstable, and the size of oil particles was double larger than the case prepared with only the yolk. Addition of xanthan gum increased, the viscosity and the stability by centrifuge so that the more stable mayonnaise could be prepared. The result of using log-normal density function by Heldmann represented that the normal size of sample adding 0.6%-soluble starch and sample N in non-adding control was increased, while those of sample adding xanthan gum and soluble starch at the same time didn't change.