• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.707-722
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• 1998

This paper evaluates a new clinical trial designs for low infection rate disease. This type of sparse disease reaction makes the traditional two sample t-test or Wilcoxon rank-sum test inefficient compared to a new test suggested. The new test, which is based solely on the larger changes, is shown to be more effective than existing method by simulation for small samples. However, this test can be shown to be connected to the locally most powerful rank test under certain practical conditions. This design is motivated in testing the treatment effects in periodontal disease research.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.191-197
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• 2003

This paper considers the independence test for two stationary infinite order autoregressive processes. For a test, we follow the empirical process method devised by Hoeffding (1948) and Blum, Kiefer and Rosenblatt (1961), and construct the Cram${\acute{e}}$r-von Mises type test statistics based on the least squares residuals. It is shown that the proposed test statistics behave asymptotically the same as those based on true errors.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.1-14
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• 2001

This paper discusses choosing the weight function of the Hardle and Mammen statistic in nonparametric goodness-of-fit test for regression curve. For this purpose, we modify the Hardle and Mammen statistic and derive its asymptotic distribution. Some results on the test statistic from the wild bootstrapped sample are also obtained. Through Monte Carlo experiment, we check the validity of these results. Finally, we study the powers of the test and compare with those of the Hardle and Mammen test through the simulation.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.149-156
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• 2007

This study suggests a new method for testing seasonal unit roots in a momentum threshold autoregressive (MTAR) process. This sign test is robust against heteroscedastic or heavy tailed errors and is invariant to monotone data transformation. The proposed test is a seasonal extension of the sign test of Park and Shin (2006). In the case of partial seasonal unit root in an MTAR model, a Monte-Carlo study shows that the proposed test has better power than the seasonal sign test developed for AR model.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.85-90
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• 2002

Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course experiments in which gene expression is monitored over time we are interested in testing gene expression profiles for different experimental groups. We propose a statistical test based on the ANOVA model to identify genes that have different gene expression profiles among experimental groups in time-course experiments. Using this test, we can detect genes that have different gene expression profiles among experimental groups. The proposed model is illustrated using cDNA microarrays of 3,840 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

• Journal for History of Mathematics
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• v.26 no.4
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• pp.277-299
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• 2013

It was not until the early twentieth century that statistics emerged as an independent academic discipline. The developments of statistical theory and methods would not have been possible without heated controversies among founding fathers. One of them, controversy on the statistical test between R. A. Fisher and J. Neyman, E. S. Pearson had been very fierce and long-lasting. On the other hand it was in the early twentieth century that psychologists began to utilize statistical test which was a hybrid of tests developed by Fisher and Neyman-Pearson. By considering the history of fields such as psychology, we can see distinctive characteristics specific to the history of statistics.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.325-332
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• 2003

This study was to develop a system for grading apples by their color using statistical image processing. T-test was used to detect edges in apple images and the chain code method was used for contour coding. The histogram and mean gray level of each RGB channel in a ring-shaped region was used to compare apple colors to reference apple color.

• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.171-175
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• 1990

A diagnostic test for detecting nonconstant variance in mixed linear models based on the score statistic is derived through the technique of model expansion, and compared to the log likelihood ratio test.

• Korean Journal of Oriental Medicine
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• v.18 no.3
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• pp.127-132
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• 2012

Background and Purpose : This study was to investigate statistical validities and trends of previously reported papers that used various statistical techniques such as t-test and analysis of variance. Methods : To analyze the statistical procedures, 38 original articles using those statistical methods were selected from Journal of Korea Institute of Oriental Medicine(JKIOM) published from 2010 to 2012. Results : Analysis of variance and t-test were used in 20 papers (38.5%), 16 papers (30.8%) of 52 papers. Four articles(10.5%) did not report ${\alpha}$ values and nineteen papers(50.0%) of 38 ones were not tested for normal distribution. Five papers (13.2%) misused t-test and 3 papers (7.9%) did not carry out the multiple comparison. Conclusions : To improve the quality of JKIOM, The participation of statisticians in research design will reduce the significant errors in statistical interpretation of the results.

• Korean Journal of Oriental Medicine
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• v.14 no.2
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• pp.87-91
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• 2008

Background and Purpose: The purpose of this study was investigate statistical validities of previously reported articles that used various statistical techniques such as t-test and analysis of variance. Methods: To analyze the statistical procedures, 66 original articles using those statistical methods were selected from "Korean Journal of Oriental Medicine(KJOM)" published from 1995 to 2007. Results: Twenty-one articles(32%) did not report correct p-values, 33 articles(50%) used mean${\pm}$standard error(mean${\pm}$SE) and 11 articles(l7%) used mean${\pm}$standard deviation(mean${\pm}$SD). Fifty-two articles(95%) of 55 ones which were tested for normal distribution made an error in describing normal distribution. Seventeen articles misused t-test and 12 articles did not carry out the multiple comparison. Conclusions: The training of researchers with clinical statistics or the participation of statisticians in research design will reduce the significant errors in statistical interpretation of the results.