• 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.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.135-143
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• 1996

In surveys on certain social problems which are sensitive in nature, many techniques have been introduced in order to protect evasive or untruthful answers. We suggest a multiple trial randomized response technique(MRRT) and it turns out that MRRT is feasible and more efficient by reducing the variance of the estimate than single trial RRT's investigated by Warner(1965), Mangat & Singh(1990), Mangat(1994).

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.27-41
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• 1995

In this paper, the proportion of durg-abuse and gas/bond-inhalation among the high school students in Kwangju and Chonnam has been estimated using the survey of the Black-Box method and randomized response technique. We have analyzed empirically the effects of both methods for the surveys of sensitive characters.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.247-256
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• 2003

In this study, we systemize the theoretical validity for applying RRM 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 costs 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. We apply the three-stage cluster RRM to field survey and suggest some necessary points for practical use.

• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.157-167
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• 1992

This paper presents a new two-stage randomized response model to protect greater privacy of respondents for the sensitive characters. The conditions when the proposed model will be more efficient than Warner model, Liu-Chow's multiple trial model and Mangat-Singh model have been obtained for the case when the respondents are truthful in their answer, and the efficiency of the proposed model is also compared with Warner model, Liu-Chow's multiple trial model and Mangat-Singh model.

• Clinical Nutrition Research
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• v.13 no.3
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• pp.186-200
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• 2024

Meta-analyses have been conducted with conflicting results on this topic. Due to missing several eligible studies in previous meta-analysis by Lam et al., we conducted an extensive systematic review and dose-response meta-analysis of randomized controlled trials in this regard. A comprehensive search was conducted across various databases, including MEDLINE/PubMed, ISI Web of Knowledge, Scopus, and Google Scholar, until November 2023. Based on the analysis of 33 studies comprising 2,047 individuals, it was found that there was a significant increase in body weight for each 1 g/day increase in omega-3 lipids (standardized MD [SMD], 0.52 kg; 95% confidence interval [CI], 0.31, 0.73; I² = 95%; Grading of Recommendations Assessment, Development and Evaluation [GRADE] = low). Supplementation of omega-3 fatty acids did not yield a statistically significant impact on body mass index (BMI) (SMD, 0.12 kg/m²; 95% CI, -0.02, 0.27; I² = 79%; GRADE = very low), lean body mass (LBM) (SMD, -0.02 kg; 95% CI, -0.43, 0.39; I² = 97%; GRADE = very low), fat mass (SMD, 0.45 kg; 95% CI, -0.25, 1.15; I² = 96%; GRADE = low), and body fat (SMD, 0.30%; 95% CI, -0.90, 1.51; I² = 96%; GRADE = very low). After excluding 2 studies, the findings were significant for BMI. Regarding the results of the dose-response analysis, body weight increased proportionally by increasing the dose of omega-3 supplementation up to 4 g/day. Omega-3 fatty acid supplementation can improve body weight, but not BMI, LBM, fat mass, or body fat in cancer patients; large-scale randomized trials needed for more reliable results.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.595-603
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• 2009

Typically the standard optimal allocation method distributes the sample for each stratum considering survey cost. In case of varying survey cost for each survey unit, we need to consider more practical allocation method. In other words, according to characteristics of an individual unit, we consider the optimal dynamic allocation method which first selects the survey unit having maximum value of benefit cost ratio. In terms of this, the proposed allocation method is different from standard optimal allocation method which allocate samples for each stratum and selects the random sample according to each size of sample. This paper is considered the dynamic optimal allocation method for the stratified randomized response technique which surveys for sensitive characteristic of survey units such as drug abuse, abortion, alcoholic. We prove the practical usefulness of proposed method using the numerical example.

• 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.27 no.2
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• pp.239-247
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• 2014

For a sensitive survey in which the population is composed by several strata with quantitative attributes, we present an additive stratified quantitative attribute randomized response model which applied stratified random sampling instead of simple random sampling to the models of Himmelfarb-Edgell's additive quantitative attribute model and Gjestvang-Singh's. We also establish theoretical grounds to estimate the stratum mean of sensitive quantitative attributes as well as the over all mean. We deal with the proportional and optimal allocation problems in each suggested model and compare the relative efficiency of the suggested two models; subsequently, Himmelfarb-Edgell's model is more efficient than Gjestvang-Singh's model under the condition of stratified random sampling.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.277-292
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• 2012

The research presents an application of Balanced ANOVA (BANOVA) by utilizing randomized orders for various Split-Plot Designs (SPDs) which include two cell designs, split-plot with one-way HTC (Hard to Control) factor, split-plot with two-way HTC factor, split-split-plot design and nested design. In addition, four MINITAB examples of 2-level split-plot designs based on the number of blocks and the type of whole-plots are presented for practitioners to obtain comprehensive understanding. Furthermore, the geometrical interrelated properties among three typical Designs of Experiments (DOE), such as Factorial Design (FD), Response Surface Design (RSD), and Mixture Design (MD) are discussed in this paper.