• Journal of the Korean Statistical Society
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• v.15 no.1
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• pp.26-30
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• 1986

Basu (1980) examined Fisher Randomization Test (FRT) of matched pair experimental data with critical point of view. Additionally, Lane (1980) pointed out that "the experimenter may be interested in a weaker notion of equality between two treatments, " than the notion of equality which FRT relies on. In this study, a randomization test is developed so that it can test a weaker hypothesis of equality. equality.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.781-792
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• 2009

At an early stage of genomic investigations, a small sample of microarrays is used in gene expression experiments to identify small subsets of candidate genes for a further accurate investigation. Unlike the statistical analysis methods for a large sample of microarrays, an appropriate statistical method for identifying small subsets is a randomization test that provides exact P values. These exact P values from a randomization test for a small sample of microarrays are discrete. The possible existence of differentially expressed genes in the sample of a full set of genes can be tested for the null hypothesis of a uniform distribution. Subsets of smaller P values are of prime interest for a further accurate investigation and identifying these outlier cells from a multinomial distribution of P values is possible by M test of Fuchs et al. (1980). Above all, the genome-wide gene expressions in microarrays are correlated, but the majority of statistical analysis methods in the microarray analysis are based on an independence assumption of genes and ignore the possibly correlated expression levels. We investigated with simulation studies the effect that correlated gene expression levels could have on the randomization test results and M test results, and found that the effects are often not ignorable.

• The Journal of the Korean dental association
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• v.53 no.7
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• pp.476-484
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• 2015

Purpose: This study intended to analyze the validity of clinical effectiveness data of clinical trials testing systemic titrated extract of Zea Mays L. unsaponifiable fraction chemotherapeutic agent. Material and Methods: Among 5 clinical trials claimed as proof of clinical effectiveness on the Web site of the manufacturer of this chemotherapeutic agent, a review of 4 clinical trials, written in either Korean or English, was conducted. Data were extracted from studies for the following variables: year of publication, age, sample size, follow-up period, combination with contemporary periodontal treatments, randomization, randomization check, blinded measurement, and statistical test type. Results: The study subjects' age intervals were too diverse to decide a common target population to generalize the findings. No study stated clearly the rationale for the sample size determination. Follow-up period to observe the start of clinical effectiveness was inconsistent and decided without any rationale of pathophysiological latent period. Randomization to make the comparisons on the same start line was performed but failed in a study. Randomization effect was not checked in 4 studies. Performance of blinded measurement of clinical outcomes to prevent bias was unclear in 2 studies. Type of statistical test was inappropriate in 3 studies. Conclusions: Based on the analysis of the validity of data on clinical and demographic variables, the four available clinical trials have not demonstrated compelling evidence of therapeutic effectiveness of systemic titrated extract of Zea Mays L. unsaponifiable fraction chemotherapeutic agent to improve prognosis of periodontal disease either with the contemporary periodontal treatment or without it.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.543-553
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• 2016

The validity of statistical inference depends on proper randomization methods. However, even with proper randomization, we can have imbalanced with respect to important characteristics. In this paper, we introduce a method based on ranked auxiliary variables for treatment allocation in crossover designs using Latin squares models. We evaluate the improvement of the efficiency in treatment comparisons using the proposed method. Our simulation study reveals that our proposed method provides a more powerful test compared to simple randomization with the same sample size. The proposed method is illustrated by conducting an experiment to compare two different concentrations of titanium dioxide nanofiber (TDNF) on rats for the purpose of comparing weight gain.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.219-227
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• 2001

Another approach (multi-parameter measurement method) of interlaboratory studies of test methods is presented. When the unrestricted normal likelihood for the fixed latent variable model is unbounded, we propose a me쇙 of restricting the parameter space by formulating realistic alternative hypothesis under which the likelihood is bounded. A simulation study verified the claim of conservatism of level of significance based on assumptions about central chi-square distributed test statistics and on Bonferroni approximations. We showed a randomization approach that furnished empirical significance levels would be better than a Bonferroni adjustment.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.67-75
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• 2001

A completely randomized growth curve model was defined by Zerbe(1979). We propose the fully significant difference procedure for multiple comparisons of completely randomized growth curve model. The standard F test is useful tool to multiple comparisons of the completely randomized growth curve model. The proposed method is applied to experimental data.

• The KIPS Transactions:PartC
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• v.18C no.2
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• pp.89-96
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• 2011

ASR is an excellent program security technique that protects various data memory areas without run-time overhead. ASR hides the addresses of variables from attackers by reordering variables within a data memory area; however, it can be broken by brute force attacks because of a limited data memory space. In this paper, we propose Multiple ASR to overcome the limitation of previous ASR approaches. Multiple ASR separates a data memory area into original and duplicated areas, and compares variables in each memory area to detect an attack. In original and duplicated data memory areas variables are arranged in the opposite order. This makes it impossible to overwrite the same variables in the different data areas in a single attack. Although programs with Multiple ASR show a relatively high run-time overhead due to duplicated execution, programs with many I/O operations such as web servers, a favorite attack target, show 40~50% overhead. In this paper we develop and test a tool that transforms a program into one with Multiple ASR applied.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.583-595
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• 2005

Contingency tables are used to compare counts of n-grams to determine if the n-gram is a true collocation, meaning that the words that make up the n-gram are highly associated in the text. Some statistical methods for identifying collocation are used. They are Kulczinsky coefficient, Ochiai coefficient, Frager and McGowan coefficient, Yule coefficient, mutual information, and chi-square, and so on. But the main problem is that these measures are based ell the assumption of a nor-mal or approximately normal distribution of the variables being sampled. While this assumption is valid in most instances, it is not valid when comparing the rates of occurrence of rare events, and texts are composed mostly of rare events. In this paper we have simply reviewed some statistics about testing association of two words. Some randomization tests to evaluate the significance level in analyzing collocation in large corpora are proposed. A related graph can be used to compare different lest statistics that ran be used to analyze the same contingency table.

• The Mathematical Education
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• v.38 no.2
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• pp.165-172
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• 1999

$\sub$e/$\^$2/, that were results from those three sources of such imperfection. Especially to eliminate the differences in severity among many raters the randomization procedure of raters sample was very effective in enhancing the reliability of ratings with comparatively small groups of examinees and raters. And we also introduced the new rating methods, i.e. the 2-step diagnostic procedures to check the sizes of the reliability stability of raters and the sore adjustment method to enumerate the optimal mean values in rating the examinees.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.339-352
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• 1997

Chi-square test based on large sample theory is inappropriate for testing the row homogeneity in two-way contingency table with several sparse cells. For that case, exact testing methods has been developed in the literature and implemented in StatXact(1991). However, considerable computing time is inevitable for moderate size tables. So, Monte Carlo approximation is recommended frequently. In this study, we propose a simple algorithm for generating two-way random tables with fixed row and column margins for small sample chi-square test. Also, we develop “Turkey-type” method for multiple between-row comparisons.