• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.19-24
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• 2002

The two-way balanced one-level rotation design has been discussed (Park, Kim and Choi, 2001), where the two-way balancing is done on interview time in monthly sample and rotation group. We extend it to three-way balanced multi-level design under the most general rotation system. The three-way balancing is accomplished on interview time not only in monthly sample and rotation group but also in recall time. We present the necessary condition and rotation algorithm which guarantee the three-way balancing. We propose multi-level composite estimators (MCE) from this design and derive their variances and mean squared errors (MSE), assuming the correlation from the measurements of the same sample unit and three types of biases in monthly sample.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.367-374
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• 1997

In panel surveys it is necessary to manage both sampling frame and sample units across time. When sample is updated according to the change of its frame, it should be incorporated in the estimation procedure. This paper derives the bias of the conventional estimator caused by neglecting the change of sample, and provides a bias-adjusted estimator with its variance.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1557-1564
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• 2017

We take genomic sequences of high-dimensional low sample size (HDLSS) without ordering of response categories into account. When constructing an appropriate test statistics in this model, the classical multivariate analysis of variance (MANOVA) approach might not be useful owing to very large number of parameters and very small sample size. For these reasons, we present a pseudo marginal model based upon the Gini-Simpson index estimated via Bayesian approach. In view of small sample size, we consider the permutation distribution by every possible n! (equally likely) permutation of the joined sample observations across G groups of (sizes $n_1,{\ldots}n_G$). We simulate data and apply false discovery rate (FDR) and positive false discovery rate (pFDR) with associated proposed test statistics to the data. And we also analyze real SARS data and compute FDR and pFDR. FDR and pFDR procedure along with the associated test statistics for each gene control the FDR and pFDR respectively at any level ${\alpha}$ for the set of p-values by using the exact conditional permutation theory.

• Journal of Korean Society for Quality Management
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• v.29 no.1
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• pp.1-10
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• 2001

We consider the problem of detecting special variations in multivariate $T^2$-control chart when two or more multivariate outliers are present. Since a multivariate outlier may reflect slippage in mean, variance, or correlation, it can distort the sample mean vector and sample covariance matrix. Damaged sample mean vector and sample covariance matrix have difficulty in examining special variations clearly, An alternative to detection outliers or special variations is to use robust estimators of mean vector and covariance matrix that are less sensitive to extreme observations than are the standard estimators $\bar{x}$ and $\textbf{S}$. We applied popular minimum volume ellipsoid(MVE) and minimum covariance determinant(MCD) method to estimate mean vector and covariance matrix and compared its results with standard $T^2$-control chart using simulated multivariate data with outliers. We found that the modified $T^2$-control chart based on the above robust methods were more effective in detecting special variations clearly than the standard $T^2$-control chart.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.265-278
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• 1998

In this paper, we suggest two-phase adaptive cluster sampling schemes. The main feature of the two-phase sampling is that the information collected in the first phase sample is utilized in the selection of the second phase sample. The conventional two-phase sampling is, however, not sufficient to increase efficiency when the population of interest is rare and clustered. In the proposed sampling scheme, the first phase sample is selected with adaptive cluster sampling procedure and the second phase sample is selected by PPSWR and $\pi$PS sampling. We investigate unbiased estimators of population total and their variance for the proposed sampling schemes respectively. Finally we compare these suggested sampling schemes using numerical examples .

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.297-310
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• 2002

Liang and Zeger proposed generalized estimating equations(GEE) for analyzing repeated data which is discrete or continuous. GEE model can be extended to model for repeated categorical data and its estimator has asymptotic multivariate normal distribution in large sample sizes. But GEE is based on large sample asymptotic theory. In this paper, we study the properties of GEE estimators for repeated ordinal data in small sample sizes. We generate ordinal repeated measurements for two groups using two methods. Through Monte Carlo simulation studies we investigate the empirical type 1 error rates, powers, relative efficiencies of the GEE estimators, the effect of unequal sample size of two groups, and the performance of variance estimators for polytomous ordinal response variables, especially in small sample sizes.

• International Journal of Industrial Entomology and Biomaterials
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• v.22 no.1
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• pp.5-10
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• 2011

The effect of sample handling condition on the rheological measurement of regenerated silk fibroin formic acid solution using parallel plate geometry was investigated. In case of loading method, the loading by pouring sample solution resulted in the best reproducibility of rheological measurement. Loading with spoon showed a high variance of viscosity value at low shear rate region ($0.01{\sim}1sec^{-1}$) while loading with syringe exhibited a low reproducibility of viscosity at high shear region ($1{\sim}100sec^{-1}$) with a disappearance of shear thinning phenomenon. It was revealed that the sample loading with small extra amount lead to the most reproducible result. The sample loading with the exact amount for the measuring plate resulted in a lack of reproducibility of high shear viscosity, while the loading with large extra volume produced a limited consistency of low shear viscosity. It was turned out that 3 min. of waiting time before measurement was the optimum condition for reliable result. When the waiting time was less than 1 min., the low shear viscosity was obtained with a lack of consistency. On the other hand, the sample solution started drying when the waiting time increased up to 5 min.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.605-618
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• 2007

Adaptive sampling design is the selection procedure which depends on observed values of the variable of interest. It is the method which could be applied to the rare and unapproachable population. Adaptive cluster sampling strategies are more efficient than simple random sampling on equivalent sample size. Adaptive sampling with new estimators through the Rao-blackwell method have lower variance than Horvitz-Thompson (HT) and Hansen-Hurwitz (HH). Also, to determine suitable sample size, it was used expected sample and the method finding appropriate sample size by changing initial sample size were studied.

• Asia pacific journal of information systems
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• v.15 no.4
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• pp.61-87
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• 2005

This paper has two primary objectives: (1) to propose a comprehensive theoretical model that incorporates valuable insights from two complementary streams of research, and (2) to empirically test the model that explain the task-media fit and satisfaction of customer contact center users. The comprehensive model was tested using LISREL analysis on the sample of 232 users who have experience with the customer contact center. The model was supported in customer contact center context, accounting for 29% of the variance in the task-media fit, 53% of the variance in the perceived ease of use, 61% of the variance in the perceived usefulness, and 52% of the variance in the user satisfaction. The results showed that the task-media fit, the perceived ease of use, and the perceived usefulness play a significant role in influencing the user satisfaction of the customer contact center. In addition, task analyzability, media richness, media interactivity, and self-efficacy were found to influence the task-media fit. The paper concludes with discussions and implications for researchers and practitioners.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.625-636
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• 2011

This paper proposes two parametric entropy estimators, the minimum variance unbiased estimator and the maximum likelihood estimator, for the lognormal distribution for a comparison of the properties of the two estimators. The variances of both estimators are derived. The influence of the bias of the maximum likelihood estimator on estimation is analytically revealed. The distributions of the proposed estimators obtained by the delta approximation method are also presented. Performance comparisons are made with the two estimators. The following observations are made from the results. The MSE efficacy of the minimum variance unbiased estimator appears consistently high and increases rapidly as the sample size and variance, n and ${\sigma}^2$, become simultaneously small. To conclude, the minimum variance unbiased estimator outperforms the maximum likelihood estimator.