• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.799-808
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• 2002

This paper aims at selecting the multi-response design with γ responses minimizing the bias error caused by fitting inadequate models to responses, where the first order models are fitted to Ρ responses fearing the quadratic bias, while to other γ- Ρ responses, the quadratic models are fitted fearing the cubic biases in the cuboidal region of interest. Under the assumption of symmetric design, by minimizing the criterion which represents the amount of error caused by fitting inadequate models, the optimum design was found to be the one having the design moments of second order and the fourth order as 1/3 and l/5, respectively. Examples of the design meeting the required conditions are given for illustration.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.408-413
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• 2003

The frequency response function(FRF) of each substructure is used for the transfer function synthesis method(TFS). The dynamic characteristics of the full system are obtained by synthesizing FRFs of each substructure. The validation of TFS depends on accuracy for FRF of each substructure. Impact hammer testing Is widely used to obtain the modal characteristics of structures However. the FRF obtained from impact hammer testing contains bias errors, such as finite record length error and leakage error of which characteristic depends on data acquisition time which we call record length. In this paper, a method to remove hose errors is proposed so as to enhance results of TFS. Numerical and experimental examples show that the FRF of full structure can be predicted nearly exactly by the method proposed in this paper.

• Journal of Korean Academy of Nursing
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• v.36 no.8
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• pp.1295-1300
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• 2006

Purpose. The purposes of this methodologic paper are to (1) describe theoretical background in conducting research across different cultures; (2) address measurement issues related to instrument administration; and (3) provide strategies to deal with measurement issues. Methods. A thorough review of the literature was conducted. A theoretical background is provided, and examples of administering instrument in studies are described. Results. When applying an instrument to different cultures, both equivalence and bias need to be established. Three levels of equivalence, i.e., construct equivalence, measurement unit equivalence, and full score comparability, need to be explained to maintain the same concept being measured. In this paper, sources of bias in construct, method, and item are discussed. Issues related to instrument administration in a cross-cultural study are described. Conclusion. Researchers need to acknowledge various group differences in concept and/or language that include a specific set of symbols and norms. There is a need to question the philosophical and conceptual appropriateness of an assessment measure that has been conceptualized and operationalized in a different culture. Additionally, testing different response formats such as narrowing response range can be considered to reduce bias.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.631-642
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• 2019

Many methods have been developed to solve problems found in sample surveys involving a large number of item non-responses that cause inaccuracies in estimation. However, the non-response adjustment method used under the assumption of random non-response generates a bias in cases where the response rate is affected by the variable of interest. Chung and Shin (2017) and Min and Shin (2018) proposed a method to improve the accuracy of estimation by appropriately adjusting a bias generated when the response rate is a function of the variables of interest. In this study, we studied a case where the response rate function is linear and the error of the super population model follows normal distribution. We also examined the effect of the number of stratum population on bias adjustment. The performance of the proposed estimator was examined through simulation studies and confirmed through actual data analysis.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.923-936
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• 2021

A large number of non-responses are occurring in the sample survey, and various methods have been developed to deal with them appropriately. In particular, the bias caused by non-ignorable non-response greatly reduces the accuracy of estimation and makes non-response processing difficult. Recently, Chung and Shin (2017, 2020) proposed an estimator that improves the accuracy of estimation using parametric super-population model and response rate model. In this study, we suggested a bias corrected non-response mean estimator using a nonparametric function generalizing the form of a parametric super-population model. We confirmed the superiority of the proposed estimator through simulation studies.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.375-389
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• 2019

Sample attrition according to a long-term tracking reduces the representativeness of the sample data in a panel study. Most panel surveys in South Korea and other countries have prepared response adjustment weights in order to solve problems regarding representativeness due to sample attrition. In this paper, we divided the panel data into continuous response group and non-continuous response group according to response patterns and considered a weighting adjustment method to reduce the bias of the non-continuous response group. A simulation indicated that the proposed composite estimation type weighting method, which reflected the characteristics of non-continuous response groups, could be more efficient than other weighting methods in terms of reducing non-response bias. As a case study, the proposed methods are applied to the Korean Longitudinal Study of Ageing (KLoSA) data of the Korea Employment Information Service.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.485-499
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• 2022

Controlling the total survey error including sampling error and non-sampling error is very important in sampling design. Non-sampling error caused by non-response accounts for a large proportion of the total survey error. Many studies have been conducted to handle non-response properly. Recently, a lot of non-response imputation methods using machine learning technique and traditional statistical methods have been studied and practically used. Most imputation methods assume MCAR(missing completely at random) or MAR(missing at random) and few studies have been conducted focusing on MNAR (missing not at random) or NN(non-ignorable non-response) which cause bias and reduce the accuracy of imputation. In this study, we propose a non-response imputation method that can be applied to non-ignorable non-response. That is, we propose an imputation method to improve the accuracy of estimation by removing the bias caused by NN. In addition, the superiority of the proposed method is confirmed through small simulation studies.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.10
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• pp.912-917
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• 2007

Many electrochemical power devices such as solid state batteries and solid oxide fuel cell have been studied and developed for solving energy and environmental problems. An amperometric gas sensor usually generates sensing signal of electric current along the proportion of the concentration of target gas under the condition of limiting current. For narrow variations of gas concentration, the amperometric gas sensor can show higher precision than a potentiometric gas sensor does. In additional, cross sensitivities to interfering gases can possibly be mitigated by choosing applied voltage and electrode materials properly. In order to improve the sensitivity to $NO_2$, the device was attached with Au reference electrode to form the amperometric gas sensor device with three electrodes. With the fixed bias voltage being applied between the sensing and counter electrodes, the current between the sensing and reference electrodes was measured as a sensing signal. The response to $NO_2$ gas was obviously enhanced and suppressed with a positive bias, respectively, while the reverse current occurred with a negative bias. The way to enhance the sensitivity of $NO_2$ gas sensor was thus realized. It was shown that the response to $NO_2$ gas could be enhanced sensitivity by changing the bias voltage.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.9-26
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• 1995

In surveys on sensitive issues which respondents are unwilling to answer, response bias usually occur since respondents tend to answer untruthfully or evade answer. Warner(19650 introduced the Randomized Response Technique (RRT) which protected the privacy of the individual respondent to reduce these response biases. Though this technique are theoretically good it has some problems in applying this technique to field survey. Therefore in order to apply easily RRT to practical survey we present the practical plan through comparing and analyzing the several cases which RRT was applied. Also we take the field survey according to this plan.

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1377-1391
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• 2023

When sensitive topics such as gambling habits, drug addiction, alcoholism, tax evasion tendencies, induced abortions, drunk driving, past criminal involvement, and homosexuality are the focus of open or direct surveys, it becomes challenging to obtain accurate information due to nonresponse bias and response bias. People often hesitate to provide truthful answers. Warner introduced an ingenious method to address this issue. In this study, a new and unrelated randomized response model is proposed to eliminate misleading responses and nonresponses caused by the stigma associated with the attribute being investigated. The proposed randomized response model allows for the estimation of the population percentage with the sensitive characteristic in an unbiased manner. The characteristics and recommendations of the proposed randomized response model are examined, and numerical examples are provided to support the findings of this study.