• The Korean Journal of Applied Statistics
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• v.4 no.2
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• pp.179-193
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• 1991

In this paper, we introduce various methods of PR techniques initiated by S. Warner in 1960's and examine the maximum likelihood estimator for them. One of the main subjects of this paper is to represent Warner model, Unrelated Question Model, and Multi-Proportion Model in linear model. The other subject is to study the inference of PR model by using the Bayesian Approach.

• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.55-65
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• 2003

In this study, we systemize the theoretical validity for applying unrelated question model to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the cost are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.53-66
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• 1993

A Bayesian approach is suggested to the multi-proportions randomized response model. O'Hagan's (1987) Bayes linear estimator is extended to the inference of unrelated question-type randomized response model. Also some numerical comparisons are provided to show the performance of the Bayes linear estimator under the Dirichlet prior.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2895-2905
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• 2018

We present a mixed multiplicative quantitative randomized response model which added a unrelated quantitative attribute and forced answer to the multiplicative model suggested by Bar-Lev et al. (2004). We also try to set up theoretical grounds for estimating sensitive quantitative attribute according to circumstances whether or not the information for unrelated quantitative attribute is known. We also extend it into the stratified mixed multiplicative quantitative randomized response model for stratified population along with two allocation methods, proportional and optimum allocation. We can see that the various quantitative randomized response models such as Eichhorn-Hayre's model (1983), Bar-Lev et al.'s model (2004), Gjestvang-Singh's model (2007) and Lee's model (2016a), are one of the special occasions of the suggested model. Finally, We compare the efficiency of our suggested model with Bar-Lev et al.'s (2004) and see that the bigger the value of $C_z$, the more the efficiency of the suggested model is obtained.

• Communications for Statistical Applications and Methods
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• v.4 no.3
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• pp.725-734
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• 1997

많은 사회과학 조사에서 분할표 형태로 얻어진 범주형 자료에는 오분류(misclassification)로 인한 오차가 내재되는 경우가 종종 있다. 질적속성 추정을 위한 확률화응답은 이러한 오분류 문제의 한 특수한 경우로 여겨지기도 한다. 그래서 확률화응답을 통한 범주형자료는 혼합된 분할표(mixed-up contingency table)로 여길 수 있는 바, 본 논문에서는 이에 대해 대수선형모형(log-linear model)을 설정하고 Chen과 Fienberg(1976)의 Iterative scaling procedure(ISP)에 의하여 얻어진 최우추정량의 극한을 이용하였다. 이 결과 Warner(1965) 형태의 대칭기법에 대해서는 Singh(1976)에 의하여 제안된 최우추정량과 같아지게 됨을 보임으로써 Warner에 의해서 제시된 추정량이 최우추정량으로 적절하지 않음을 확인해 보고, 무관질문기법에 대해서는 Greenberg, et al.(1969)에 의해서 제안된 추정량이 추정의 관점에서 최우추정량으로 적절하지 않음을 알아 보았다.

• Korean Journal of Culture and Social Issue
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• v.15 no.1
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• pp.95-132
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• 2009

Can money buy happiness? If not, what are the factors that influence happiness? What makes people happy? What are the factors that influence happiness among Korean adults? How can we better explain factors that influence happiness? These are the research questions that led to the analyses of psychological, relational, financial resources that influence happiness. To examine differences in socio-economic status, adults and elderly from three different districts that vary wealth and income were interviewed in their own home. A total of 313 respondents (male=133, female=180) between the ages of 20 through 80 completed a questionnaire that contained background information, emotional support scale and happiness scale developed by the present researcher and resiliency of efficacy developed by Bandura(1995). The results are as follows. First, monthly income influence happiness to some extent, but when the variable was excluded from the path analysis, the goodness-of-fit did not change significantly. Although those who have more money can be happier, those without much money can also be happy. These results indicate that financial resource has limited influence on happiness. In addition, monthly income did influence self-efficacy of respondents indicating that those with more money were not necessarily more confident about themselves. Second, an important factor influencing happiness is the relational resource. Emotional support was the most powerful predictor of happiness, four to five times more important than monthly income. Third, self-efficacy influenced happiness. Those respondents with higher resiliency of efficacy had higher happiness scores and the influence was two times greater than monthly income. Moreover, self-efficacy played a mediating role between emotional support and happiness. Fourth, those respondents with higher occupational achievement reported higher happiness score and the influence was two times greater than monthly income. Fifth, success of children influenced happiness score and the influence was 1.5 times greater than monthly income. Sixth, education did not directly influence happiness, but had an indirect influence through self-efficacy and occupational achievement. Seventh, age was not related to self-efficacy and happiness.