• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1289-1300
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• 2009

The double sampling scheme is effective in reducing the sampling cost. However, the doubly sampled data is contaminated by two types of error, namely false-positive and false-negative errors. These would make the statistical analysis more difficult, and it would require more sophisticate analysis tools. For instance, the Wald method for the interval estimation of a proportion would not work well. In fact, it is well known that the Wald confidence interval behaves very poorly in many sampling schemes. In this note, the property of the Wald interval is investigated in terms of the coverage probability and the expected width. An alternative confidence interval based on the Agresti-Coull's approach is recommended.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.137-144
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• 2005

In $I{\times}J$ incomplete contingency tables, the test of independence proposed by Chen and Fienberg(1974) uses $I{\times}J-1$ instead of (I-1)(J-1) degrees of freedom without providing much of an increase in the value of the test statistic. For these reasons, Chen and Fienberg tests are expected to have less power. New Wald test statistic related to the part of Chen and Fienberg test statistic is proposed using delta method. These two tests are compared through Monte Carlo studies.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.11-24
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• 1999

In this paper we propose a method to test $\textit{H}$:$\rho_i$=$\gamma_i$ for 1$\leq$$\textit{i}$$\leq$$\ell$ against $\textit{K}$:$\rho_i$$\neq$$\gamma_i$ for some ｉin k-variance component random or mixed linear model where $\rho$i denotes the ratio of the i-th variance component to the error variance and $\ell$$\leq$K. The test which we call Rao-Wald test is exact and does not depend upon nuisance parameters. From a numerical study of the power performance of the test of the interaction effect for the case of a two-way random model Rao-Wald test was seen to be quite comparable to the locally best invariant (LBI) test when the nuisance parameters of the LBI test are assumed known. When the nuisance parameters of the LBI test are replaced by maximum likelihood estimators Rao-Wald test outperformed the LBI test.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.208-213
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• 2014

National-wide and/or large scale sample surveys generally use complex sample design. Traditional Pearson chi-square test is not appropriate for the categorical complex sample data. Rao-Scott suggested an adjustment method for Pearson chi-square test, which uses the average of eigenvalues of design matrix of cell probabilities. This study is to compare the efficiency of Rao-Scott first order adjusted test to Wald test for homogeneity between two populations using 2009 Gyeongnam regional education offices's customer satisfaction survey (2009 GREOCSS) data. The 2009 GREOCSS data were collected based on stratified three-stage cluster sampling with probability proportional to size. The empirical results show that the Rao-Scott adjusted test statistic using only the variances of cell probabilities is very close to the Wald test statistic, which uses the covariance matrix of cell probabilities, under the 2009 GREOCSS data based. However it is necessary to be cautious to use the Rao-Scott first order adjusted test statistic in the place of Wald test because its efficiency is decreasing as the relative variance of eigenvalues of the design matrix of cell probabilities is increasing, specially more when the number of degrees of freedom is small.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.171-181
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• 2006

The Wald confidence interval has been considered as a standard method for the difference of proportions. However, the erratic behavior of the coverage probability of the Wald confidence interval is recognized in various literatures. Various alternatives have been proposed. Among them, Agresti-Caffo confidence interval has gained the reputation because of its simplicity and fairly good performance in terms of coverage probability. It is known however, that the Agresti-Caffo confidence interval is conservative. In this note, a confidence interval is developed using the weighted Polya posterior which was employed to obtain a confidence interval for the binomial proportion in Lee(2005). The resulting confidence interval is simple and effective in various respects such as the closeness of the average coverage probability to the nominal confidence level, the average expected length and the mean absolute error of the coverage probability. Practically it can be used for the interval estimation of the difference of proportions for any sample sizes and parameter values.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.1-11
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• 2012

When the microarray experiment developed, main interest was limited to detect differentially expressed genes associated with a phenotype of interest. However, as human diseases are thought to occur through the interactions of multiple genes within a same functional category, the unit of analysis of the microarray experiment expanded to the set of genes. For the phenotype of censored survival time, Gene Set Enrichment Analysis(GSEA), Global test and Wald type test are widely used. In this paper, we modified the Wald type test by adopting normal score transformation of gene expression values and developed a parametric test which requires much less computation than others. The proposed method is compared with other methods using a real data set of ovarian cancer and a simulation data set.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.971-984
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• 2015

Imputation procedures fill-in missing values, thereby enabling complete data analyses. Fully efficient fractional imputation (FEFI) and multiple imputation (MI) create multiple versions of the missing observations, thereby reflecting uncertainty about their true values. Methods have been described for hypothesis testing with multiple imputation. Fractional imputation assigns weights to the observed data to compensate for missing values. The focus of this article is the development of tests of independence using FEFI for partially classified two-way contingency tables. Wald and deviance tests of independence under FEFI are proposed. Simulations are used to compare type I error rates and Power. The partially observed marginal information is useful for estimating the joint distribution of cell probabilities, but it is not useful for testing association. FEFI compares favorably to other methods in simulations.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.445-455
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• 2011

Although misclassified binary data occur frequently in practice, the statistical methodology available for the data is rather limited. In particular, the interval estimation of population proportion has relied on the classical Wald method. Recently, Lee and Choi (2009) developed a new confidence interval by applying the Agresti-Coull's approach and showed the efficiency of their proposed confidence interval numerically, but a theoretical justification has not been explored yet. Therefore, a Bayesian model for the misclassified binary data is developed to consider the Agresti-Coull confidence interval from a theoretical point of view. It is shown that the Agresti-Coull confidence interval is essentially a Bayesian confidence interval.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.6
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• pp.11-25
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• 2009

A method of instrumentally estimating the seismic intensity (MMI) based on Fourier Acceleration Spectrum, which is the so-called 'FAS MMI method' of Sokolov and Wald (2002), was considered for its applicability to Korea. In order to implement the FAS MMI method, the empirical models of mean (m) and standard deviation (${\sigma}$) for Korea were derived for MMI ${\leq}$ IV according to individual seismic intensity by using the site-consistent horizontal FAS of 580 records from 65 isoseismal maps prepared based on the reported MMI of Korea Meteorological Administration. The site-consistent FAS at a site were obtained by correcting the observed FAS for the difference of the site amplification function relative to that of the target site of Class D station (Yun and Suh, 2007) which was evaluated to be a representative site for the generic soil profile of Korea. The FAS m model for MMI ${\leq}$ IV follows the overall linear relation in log space according to seismic intensities, featuring the FAS mean model for MMI = IV similar to that of the global model of Sokolov and Wald (2002). The ${\sigma}$-values of the FAS model are found to be greater than those of the global model for MMI ${\geq}$ V, while significantly lower than those of the global model for MMI = IV.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.63-76
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• 2001

An adaptive estimation and testing method is proposed for comparing dispersions among several ordered groups. Based upon the large sampling theory for nonparametric quartile estimators, we derive the order restricted estimators and construct a simple test statistic. This test statistic has a mixture of several chi-square distributions as its asymptotic null distribution. The proposed test is illustratively applied to survival time data for the patients with carcinoma of the oropharynx.