• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.403-410
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• 1998

Mangat(1994)는 Mangat-Singh(1990)이 제안한 2단계 관련질문모형의 사용 절차를 좀 더 단순화시킨 개선된 관련질문모형을 제안하여 민감한 질적 속성을 추정하였다. 본 논문에서는 Mangat의 개선된 관련질문모형을 양적속성의 무관질문모형으로 확장하고자 한다. 또한, 제안한 모형이 Greenberg et al.의 양적속성의 무관질문모형이나 최경호(1996)가 제안한 2단계 양적속성의 무관질문모형보다 효율적이 되는 조건을 제시하였다.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.897-906
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• 2016

We augment an unrelated quantitative attribute to Bar-Lev et al.'s model (2004) which is composed of sensitive quantitative variable and scrambled one to present a multiplicative unrelated quantitative randomized response model(MUQ RRM). We also establish theoretical grounds to estimate the sensitive quantitative attribute according to circumstances irrespective of known or unknown unrelated quantitative attribute. Finally, we explore the relationship among the suggested model, Eichhorn-Hayre model, Bar-Lev et al.'s model and Gjestvang-Singh's model, and compare the efficiency of our model with Bar-Lev et al.'s model.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.27-38
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• 1995

In the surveys of sensitive issues of the population that is composed of several unknown-size stratum, we propose the unrelated question model with quantitative attribute by using stratified double sampling. And, we consider two types of sample allocations under the fixed cost, which are the proportional allocation, the optimum allocation. In efficiency, the proosed model is inferior to the unrelated question model with quantitative attribute by stratified sampling in case of the size of each stratum is known. But we find that efficiency of the proposed model is increased, when the selecting probability of sensitive question p is small and first stage sample size n' is large.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.141-150
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• 1998

In this paper, we developed one-stage cluster randomized response model for obtaining quantitative data by using the Greenberg et al. model(1971) when the population was made up of sensitive quantitative clusters. We obtained the minimum variance by calculating the cluster's size and the optimum number of sample clusters under the some given constant cost. We compared the efficiency of our model with the Greenberg et al. model by simple random sampling.

• 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.

• Journal of Korean Society of Forest Science
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• v.76 no.4
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• pp.338-347
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• 1987

The research was carried out to investigate the related phenomena, the latent structures and synthetical characteristics in various growth factors of Phyllostachys bambusoides Sieb. et Zucc. growing at Damyang gun, Chollanamdo, using multivariate analysis. 1. By synthetical characteristics in canonical correlation between height-growth factor group and diameter-growth factor group, the former was determined by the culm height ($x_1$), and the latter by the. diameter of the largest internode($x_7$). And for those between quantitative growth factor group and qualitative growth factor group, the former was determined by the surface area($x_{10}$), and the latter by the diameter of the largest internode ($x_7$). 2. The ten growth factors of bamboo culm were simplified by two principal components on the basis of accumulated proportion aimed at 90%. The first principal component($Z_1$) as a "size factor" showed high correlation with growth factors except eye-height diameter($x_5$). The second principal component($Z_2$) as a "shape factor" showed high correlation only with $x_5$. 3. The bamboo culm, and the latent phenomenon between their growth factors could be determined by two common factors showing high communality(94.16%). The ten growth factors can be grouped into two attribute factors: quantity and quality. 4. The bamboo culms can be classified into five types: total, volume, shape-quality, inferior and middle.