• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.27-38
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• 2018

Purpose: A large number of attributes with mixed levels are often considered in the conjoint analysis. In the cases where attributes have two or three levels, we research on the efficient design of survey questionnaire to estimate all the main effect and two factor interaction effects with a reasonable size of it. Methods: To reduce the number of questions in a questionnaire, the balanced incomplete block mixed level factorial design with minimum aberration was proposed by Lim and Chung (2016). Based on the number of questions and that of the respondents in that design, D-optimality criterion is adopted to find efficient designs where the main effect and two factor interaction effects are estimated. Results: The list of the number of questions and that of the respondents in efficient designs for survey questionnaire are recommended based on the D-efficiency of each design and the proposed selection criteria for the number of both questions and the respondents. By analyzing all the respondents survey data generated by the simulation study, we find the proper model. Conclusion: The proposed methods of designing survey questionnaires seem to perform well in the sense that how often the proper model is found in a simulation study where all the respondents survey data are generated by the simulation model.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.219-229
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• 2000

Oh et al.(1999) 3$\times$2 crossover design for assessing bioequivalence when two new generic drug formulations and innovator are simultaneously considered. This design is not only more efficient than 3$\times$3 one, proposed by Lee et al.(1998), in practical sense, but also more ethical in medical sense. However, the general statistical methods are not directly applicable to both designs when subjects are dropped out in the experiment, even though it is always possible in bioavailability and bioequivalence studies because of some administrative and economic reasons. In this research we propose an inference to drug effects when subjects are dropped out in the planed-for 3$\times$3 and 3$\times$2 crossover experiments. An example is given for illustration.

• Journal of Pharmaceutical Investigation
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• v.28 no.4
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• pp.231-239
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• 1998

A $3{\times}2$ crossover design is considered for the bioequivalence of two test formulations with a control. It could be considered as a better choice over $3{\times}3$ crossover design because of the cost and experimental duration. Oh et al.(1998) derived $3{\times}2$ crossover design and discussed its benefits over the typical crossover designs. We consider here the statistical models for $3{\times}2$ crossover design and show its statistical properties. The statistical procedures for the bioequivalence in $3{\times}2$ crossover design are shown through an example and the results are summarized by satisfying the 3 standards that proposed by the Korea Food and Drug Administration Guidelines for Bioequivalence.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.951-963
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• 2015

The conjoint analyst in marketing are anxious to know whether there exist synergy or antagonistic effects between two attributes. That is to say, they are interested in estimating the main effects as well as the two factor interaction effects.We research the design of survey questionnaire so that all the main effects and two factor interaction effects are estimable by employing the resolution V balanced Incomplete Block Fractional Factorial Design. We screen vital few effects, find the proper model and obtain information for efficient concepts optimization by analyzing all respondents survey data.