• Journal of Acupuncture Research
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• v.21 no.1
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• pp.176-188
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• 2004

This study was carried out to investigate statistical validity of medical articles that used various statistical techniques such as t-test, analysis of variance, correlation analysis, regression analysis and chi-square test. For study 429 original articles using those statistical methods were selected from Journal of Korean Acupuncture & Moxibusition Society published from 1984 to 2002. 429 original articles were reviewed to analyzed the statistical procedures. Results are summarized as follows : 1. In this study 93 articles(21.68%) of 429 ones didn't report statement of statistical method in detail. 2. 53 articles(12.53%) didn't report p-value in correctly, and 245 articles(57.11 %) used mean${\pm}$standard error (Mean${\pm}$SEM.) and 109 articles used mean${\pm}$standard deviation(Mean${\pm}$SD.). All of 23 articles using nonparametric statistical techniques made an error to central tendency or dispersion. 3. 175 articles(59.93%) and 14 articles(4.79%) of 292 ones made an error to description of equal variances and normal distribution. 4. 99 articles(50%) of 185 ones misused t-test and 4 articles of 5 ones misused chi-square test. 5. 28 articles(73.68%) of 38 ones using discrete variable misused parametric technique such as t-test or ANOVA. 2 articles and 1 article of 125 ones choosing paired samples misused independent t-test and Mann-Whitney U test. 6. 20 articles using analysis of variance didn't use multiple comparison.

• Korean Journal of Veterinary Research
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• v.39 no.6
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• pp.1187-1196
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• 1999

The purpose of this study is to assess the suitability of the statistical techniques employed in papers published in the Korean Journal of Veterinary Research from March 1997 to March 1999 and it is hoped that the critical assessment may be of help to other researchers preparing their works for publication. Of the 246 original papers 94 were included in the analysis. Of 62 papers with the measure of central location and dispersion of data 34 (54.8%) used them correctly : 9 (39.1%) of 23 for t-test ; 1 (33.3%) of 3 for correlation analysis ; 7 (43.8%) of 16 for analysis of variance (ANOVA) ; 5 (62.5%) of 8 for chi-square test ; 44 (71%) of 62 for description of p-value. A number of papers employed ANOVA did not perform subsequent analysis of multiple comparison. Compared to the results of others, relatively higher proportion of papers in the present study was evaluated as appropriate analysis. The reason is that papers described insufficiently on the study design were not included, and evaluation items were restricted to the cases violated seriously inherent assumptions for each statistical technique. Statistical misuse or abuse appeared in the study is due to lack of knowledge on statistics and short of its importance for improvement the quality of paper. Because an inappropriate analysis can lead the readers to misunderstand on findings, observed statistical analyses must be valid, and correctly undertaken. It is suggested that more intensive statistical refereeing are needed, and the communication should be allowed for the controversial points.

• Journal of Environmental Impact Assessment
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• v.4 no.2
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• pp.93-103
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• 1995

This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.955-959
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• 2010

The statistical analysis module is developed for the part of the new standardized geotechnical database computer program. The purpose of this module is that the geotechnical engineers can optimize the underground construction process of the underdeveloped urban area rehabilitation by this module providing the statistical information for the geotechnical decision making and risk assessment. This module will be modified to offer the statistical information sustainable for the newly adapted geotechnical limit-state design methods.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.2 s.54
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• pp.231-242
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• 2009

The baseline distribution of a structure represents the statistical distribution of dynamic response feature from the healthy state of the structure. Generally, damage-sensitive dynamic response feature of a structure manifest themselves near the tail of a baseline statistical distribution. In this regard, some researchers have paid attention to extreme value distribution for modeling the tail of a baseline distribution. However, few researches have been conducted to theoretically understand the extreme value distribution from a perspective of statistical damage assessment. This study investigates the asymptotic convergence of domain of attraction in extreme value distribution through parameter estimation, which is needed for reliable statistical damage assessment. In particular, the asymptotic convergence of a domain of attraction is quantified with respect to the sample size out of which each extreme value is extracted. The effect of the sample size on false positive alarms in statistical damage assessment is quantitatively investigated as well. The validity of the proposed method is demonstrated through numerically simulated acceleration data on a two span continuous truss bridge.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.597-603
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• 2000

A versatile dimensionality assessment index DETECT has been developed for binary item response data by Kim (1994). The present paper extends the use of DETECT to the polytomously scored item data. A simulation study shows DETECT performs well in differentiating multidimensional data from unidimensional one by yielding a greater value of DETECT in the case of multidimensionality. An additional investigation is necessary for the dimensionally meaningful clustering methods, such as HAC for binary data, particularly sensitive to the polytomous data.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.817-827
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• 2000

In this paper, we investigate the Bayesian approach to random effect binomial regression models with improper prior due to the absence of information on parameter. We also propose a method of estimating the posterior moments and prediction and discuss some general methods for studying model assessment. The methodology is illustrated with Crowder's Seeds Data. Markov Chain Monte Carlo techniques are used to overcome the computational difficulties.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.12
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• pp.1305-1311
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• 2015

A butterfly valve is a type of flow-control device typically used to regulate a fluid flow. This paper presents an estimation of the shape parameter of the Weibull distribution, characteristic life, and $B_{10}$ life for a concentric butterfly valve based on a statistical analysis of the reliability test data taken before and after the valve improvement. The difference in the shape and scale parameters between the existing and improved valves is reviewed using a statistical hypothesis test. The test results indicate that the shape parameter of the improved valve is similar to that of the existing valve, and that the scale parameter of the improved valve is found to have increased. These analysis results are particularly useful for a reliability qualification test and the determination of the service life cycles.

• Toxicological Research
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• v.17
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• pp.17-24
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• 2001

Risk assessment is useful tool making good decisions on the risks of certain hazardous com-pound and suggests safe margin through scientific process using toxicological data, statistical tool, exposure value and relevant variants. The goal of risk management is to protect the public health from hazardous compound based on result of risk assessment having reality. For the suggestion of exact man-aging information, risk assessment must be designed to represent a "plausible estimate" of the exposure to the individuals and to minimize uncertainty. Risk assessment methodology and knowledge are expected to change more rapidly than before and up-to-date methodology should be applied in regulatory aspects through the Agency. For the useful application of risk assessment, the communication between the risk assessor and the risk manager is needed before the initiation of the risk assessment and upon its completion. Generally, the risk assessment itself as a practical tool in the regulatory decision making process would be regarded with social economic impact.ic impact.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.417-425
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• 1994

Although animal studies have been used most often for quantitative risk assessment, it is generally recognized that well-conducted epidemiologic studies would provide the best basis for estimating human risk. However, there are several features related to the design and analysis of epidemiologic studies that frequently limit their usefulness for quantitating risks. The lack of accurate information on exposure in epidemiologic studies is perhaps the most frequently cited limitation of these studies for risk assessment. However. other features of epidemiologic study design, such as statistical power, length of follow-up, confounding, and effect modification, may also limit the inferences that can be drawn from these studies. Furthermore, even when the aforementioned limitations are overcome, substantial uncertainty exists concerning the choice of an appropriate statistical (or biologic) model for extrapolation beyond the range of exposures observed in a particular study. This paper focuses on presenting a review and discussion of the methodologic issues involved in using epidemiologic studies for risk assessment. This review concentrates on the use of retrospective, cohort, mortality studies of occupational groups for assessing cancer risk because this is the most common application of epidemiologic data for quantitative risk assessment (QRA). Epidemiologic data should not be viewed as a panacea for the problems inherent in using animal bioassay data for QRA. Rather, information that can be derived from epidemiologic and toxicologic studies complement one another, and both data sources need to be used to provide the best characterization of human risk.