• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.641-647
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• 2020

The 2 × 3 crossover design, a modified version of the 3 × 3 crossover design, is considered to compare the bioavailability of two generic candidates with a reference drug. The 2 × 3 crossover design is more economically favorable due to decrease in the number of sequences, rather than conducting a 3×3 crossover trial or two separate 2 × 2 crossover trials. However, when using a higher-order crossover trial, the risk of drop-outs and withdrawals of subjects increases, so the suitable statistical inferences for missing data is needed. The bioequivalence model of a of 2×3 crossover trial with missing data is defined and the statistical procedures of assessing bioequivalence is proposed. An illustrated example of the 2 × 3 trial with missing data is also presented with discussion.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.87-105
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• 2020

Statistical engineering contains the design of experiments, quality control/management, and reliability engineering. R is a free software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. R package has many functions and libraries for statistical engineering. We can use R package as a useful tool for statistical engineering. This paper shows the applications of R package for statistical engineering and suggests a R Task View for statistical engineering.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.601-610
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• 1999

Crossover design is officially except for special occasions recommended by KFDA and FDA for assessing Bioequivalence between two drugs one for reference and the other for innovator. Such design is regarded as a special case of latin square split-polt or repeated measurement design and its main difference with other designing methods is that each subject in an experiment is exposed two drugs in sequence. Therefore general statistical analysis is not suitable since the model for this experiment includes carryover effect in addition to period and sequence effect. in this paper analysis for crossover model with two drugs and its interpretation are mainly discussed and an example is given for illustration.

• Journal of Korean Society for Quality Management
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• v.42 no.4
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• pp.563-578
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• 2014

Purpose: The purpose of this paper is integrated tolerance design process by advantages of engineering design and 6 sigma statistical tolerances design. Methods: Integrated tolerance design process can determine the goals by using engineer's experience and clarify tolerance by 6 Sigma statistical methods. Integrated design process can be applied by using non-linear simulations. Results: We applied integrated design process to the optical disc drive spindle motor and get good result. Conclusion: If this method is applied test method in the early stages of development, then Design can be reduced development time and cost.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.323-336
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• 1998

This thesis is to propose the method of evaluating the validity in stages on the design of a checklist based on the estimate theory of the validity on the design of a checklist and the method of evaluating the validity accordy to the purpose for usiug checklist and establish the standards of estimating the validity in stages on the checklist owing to the estimate theory with the journal, Journal of the Korean Society of Clothing and Textiles. We are emboding the statistical consulting server using the proposed estimate method of the validity and the followings we the questions to solve in future. First, there are many kinds of the statistical methods used in the fields of learing and applied technalogy. So we must establish the statistical standars required in each field and study and develope the special statistical checklists. Second, it is neded to systemize the estimate methods and standard on the validity by building the statistical consult DB, evaluate the researchers according to the degrees of statistical knowledge the validity of study design iud propose the delicate and generalized statistical methods appropriate to the ability of researchers.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.108-113
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• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.167-180
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• 2006

The statistical survey and analysis is much restricted to time, space and material. The statistical survey and analysis could hardly resume. The statistical survey and analysis is very important to create various and accurate information. The statistical survey and analysis which is not a expert knowledge have many problems in productivity of information, reliability and etc. In this paper, we study the design and Implementation of web-based statistical survey and analysis consulting system which a client meet easily a statistical expert on the web.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1314-1319
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• 2009

The design methods of mechanical systems are largely classified into deterministic methods and stochastic methods. In deterministic methods, design parameters are assumed to have fixed values. On the other hand, in stochastic methods, design parameters are assumed to be statistically distributed. When a stochastic method is employed, statistical characteristics of the populations of design variables are assumed to be known. However, very often, it is almost impossible or very expensive to obtain the statistical characteristics of the populations. Therefore a sample survey method is usually employed for stochastic methods. This paper describes the procedure of estimating the statistical characteristics of populations by employing sample data sets. An example of AFM micro cantilever beam is employed to show the effectiveness of the procedure.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.85-110
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• 2008

Ground investigation data to be used as a basis for geotechnical analysis and foundation design are usually troubled with large uncertainty, due to natural variability and limited number of data. Statistical methods can be a rational tool for handling such uncertain ground data, in particular with a view to the selection of characteristic values for estimating ground design parameters used in design. The characteristic values of soil properties for use in geotechnical design have oftenly based on not only a subjective judgment but also engineer's past acumulated experience. This paper discussed some statistical methods which can handle such intrinsic ground uncertainty data with a case design in a rational manner.

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.27-36
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• 2017

PURPOSES : The purpose of this study is to perform a reliability analysis of the proposed wind load combination which governs the design of support structures of subsidiary road facilities, and to evaluate whether the target reliability of the design is satisfied. METHODS : The statistical estimation method is applied and the design period of the support structure is used to obtain the statistical property of the wind load. In addition, the statistical properties of the strength of support structures are obtained from a literature review and simulation study. Actual support structures are designed by the proposed load combination and are used as the examples to examine if the target reliability is obtained. RESULTS : The result of the reliability analysis performed by using the statistical properties of load and resistance for the support structure in this study indicates that the proposed wind load combination satisfied the target reliability index of the design. Also, the convenience of the design is achieved by adopting the same design wind velocity given in the bridge design code by applying the wind velocity ratio defined for the design period of the support structure. CONCLUSIONS : It is presented that the design using the wind load combination proposed in this study achieved the target reliability index and the design wind load for different design periods can be conveniently defined by applying the velocity ratio proposed in this study.