• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.83-90
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• 2000

The chi-squared test statistic is usually employed for testing independence of two categorical variables in a two-way contingency table. It is well known that, under independence, the test statistic has an asymptotic chi-squared distribution under multinomial or product-multinomial models. For the case where both margins fixed, the sampling model of the contingency table is a multiple hypergeometric distribution and the chi-squared test statistic follows the same limiting distribution. In this paper, we study the difference between the small sample and large sample distributions of the chi-squared test statistic for the case with fixed margins. For a few small sample cases, the exact small sample distribution of the test statistic is directly computed. For a few large sample sizes, the small sample distribution of the statistic is generated via a Monte Carlo algorithm, and then is compared with the large sample distribution via chi-squared probability plots and Kolmogorov-Smirnov tests.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.371-385
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• 2003

In this paper, contour plot is considered as a method to explore the structure of categorical data. For this purpose, the paper suggests a method to sort two-way contingency table with respect to the expected marginals. It is found that the suggested plot provides us with valuable information for the underlying data structure. Firstly, we can investigate independency between the categories by examining the differences of expected frequency contours and observed frequency contours. With the plot, we can also visually investigate the existence of outliers inherent in the data. These properties of the suggested contour plot will be demonstrated by several sets of real data.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.15-35
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• 2020

In research on behavioral studies, significant attention has been paid to the stage-sequential process for multiple latent class variables. We now explore the stage-sequential process of multiple latent class variables using the multivariate latent class profile analysis (MLCPA). A latent profile variable, representing the stage-sequential process in MLCPA, is formed by a set of repeatedly measured categorical response variables. This paper proposes the extended MLCPA in order to explain an association between the latent profile variable and the latent group variable as a form of a two-dimensional contingency table. We applied the extended MLCPA to the National Longitudinal Survey on Youth 1997 (NLSY97) data to investigate the association between of developmental progression of depression and substance use behaviors among adolescents who experienced Authoritarian parental styles in their youth.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.755-764
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• 2006

Most graphical methods for categorical data can describe the structure of data and represent a measure of association among categorical variables. Among them the polyhedron plot represents sequential relationships among hierarchical log-linear models for a multidimensional contingency table. This kind of plot could be explored to describe the differences among sequential models. In this paper we suggest graphical methods, containing all the information, that reflect the relationship among all log-linear models in a certain hierarchical structure. We use the ideas of a correlation diagram.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.101-108
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• 1986

Computer programs for IBM PC/XT/AT or compatibles, are presented for running 9 nonparametric tests. They include sign test, Wilcoxon signed rank test, Mann-Whitney Wilcoxon test, Kruskal-Wallis test, Kolmogorov-Smirnov one sample and two sample tests, Kendall and Spearman rank correlation coefficient tests, and Chi square test for contingency table. Each program is written with BASIC language and is combined into a statistical package, 'NONPARA'. It is easily accessible through the menu programs. The alogorithms on which each test is based, are also explained and 3 examples are given.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.185-194
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• 2007

The information of covariates are available to do fully efficient fractional imputation(FEFI). The new method, FEFI with logistic regression is proposed to construct complete contingency tables. Jackknife method is used to get a standard errors of log-odds ratio from the completed table by the new method. Simulation results, when covariates have more information about categorical variables, reveal that the new method provides more efficient estimates of log-odds ratio than either multiple imputation(MI) based on data augmentation or complete case analysis.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.919-924
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• 2009

Geographical location carries information such as demography, local economy, environment, and life styles, which could be the sources of cancer occurrence. Analyzing geographical location associated with cancer occurrence can be instructive to physicians, patients, and health administrators regarding resource allocation, expenditures, prophylaxis and treatments. In this paper, we explored the correspondence relationship between geographical locations and mortality rates of the cancers using correspondence analysis and illustrated the approach with the mortality rates of the top 10 cancers in the 75 counties in Arkansas from 2001 to 2005. Geographical variations with respect to the mortality rates of cancers are evaluated across Arkansas counties. Based on the contingency table, correspondence analysis model is developed and the simple indices which indicate the degree to which the regions and the cancers affect each other are calculated. Quantitative results are visualized and mapped in two-dimensional graphs.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.117-128
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• 2003

The goal of non-inferiority experiments is to show that the new treatment is not inferior to the standard experiment. In this paper we compare the three methods of variance estimation used in the unconditional exact tests of two proportions. The size and power of the tests with each variance estimation method are compared using complete enumeration.

• Journal of Korean Society of Rural Planning
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• v.6 no.1 s.11
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• pp.50-58
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• 2000

In spite of importance of the farm area in the city, the urbanization and industrialization strongly results in decrease of the farm area. The purpose of this study is to establish an effective way of agricultural land uses by examining on the intention of the farmers based on the survey in Seoul area. The areas, the agricultural types, the landowner's ages, and farm land sizes, were surveyed and analyzed with respect to urban agricultural planning and land use planning. All the collected data were basically analyzed with Contingency Table and Chi-square Test using SAS statistical package. The structures of the intention of agricultural land uses were understood with the comparative analyses of the agricultural land owners, the agricultural land leaseholders, the areas, landowner's ages, farming types, and so on.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.725-734
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• 1997

많은 사회과학 조사에서 분할표 형태로 얻어진 범주형 자료에는 오분류(misclassification)로 인한 오차가 내재되는 경우가 종종 있다. 질적속성 추정을 위한 확률화응답은 이러한 오분류 문제의 한 특수한 경우로 여겨지기도 한다. 그래서 확률화응답을 통한 범주형자료는 혼합된 분할표(mixed-up contingency table)로 여길 수 있는 바, 본 논문에서는 이에 대해 대수선형모형(log-linear model)을 설정하고 Chen과 Fienberg(1976)의 Iterative scaling procedure(ISP)에 의하여 얻어진 최우추정량의 극한을 이용하였다. 이 결과 Warner(1965) 형태의 대칭기법에 대해서는 Singh(1976)에 의하여 제안된 최우추정량과 같아지게 됨을 보임으로써 Warner에 의해서 제시된 추정량이 최우추정량으로 적절하지 않음을 확인해 보고, 무관질문기법에 대해서는 Greenberg, et al.(1969)에 의해서 제안된 추정량이 추정의 관점에서 최우추정량으로 적절하지 않음을 알아 보았다.