• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.545-557
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• 2018

The inclusion of covariates in the model often affects not only the estimates of meaningful variables of interest but also its statistical significance. Such gap between statistical and subject-matter significance is a critical issue in huge sample studies. A popular huge sample study, the sample cohort data from Korean National Health Insurance Service, showed such gap of significance in the inference for the effect of obesity on cause of mortality, requiring careful consideration. In this regard, this paper proposes a sample size calibration method based on a Monte Carlo t (or z)-test approach without Monte Carlo simulation, and also proposes a test procedure for subject-matter significance using this calibration method in order to complement the deflated p-value in the huge sample size. Our calibration method shows no subject-matter significance of the obesity paradox regardless of race, sex, and age groups, unlike traditional statistical suggestions based on p-values.

• IE interfaces
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• v.6 no.1
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• pp.55-65
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• 1993

A nonstandard instrument used in the filed frequently becomes out-of-calibration due to environmental noise, misuse, aging, etc. A substantial amount of loss may result if such nonstandard instrument is used to check product quality and performance. Traditional periodic calibration at the calibration center is not capable of detecting out-of-calibration status while the instrument is in use, and therefore, statistical methods need to be developed to check the status of a nonstandard instrument in the field between calibrations. Developed in this paper is a unified measurement assurance model in which statistical calibration at the calibration center and measurement assurance test in the filed are combined. We developed statistical procedures to detect changes in precision and in the coefficients of the calibration equation. Futher, computational experiments are conducted to evaluate how the power of test varies with respect to the parameters involved. Based upon the computational results we suggest procedures for designing effective measurement assurance tests.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.265-277
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• 1999

Classical and inverse estimation methods are two well known methods in statistical calibration problems. When there are outliers, both methods have large MSE's and could not estimate the input value correctly. We suggest median calibration estimation based on the LD-statistics. To investigate the robust performances, the influence function of the median calibration estimator is calculated and compared with other methods. When there are outliers in the response variables, the influence function is found to be bounded. In simulation studies, the MSE's for each calibration methods are compared. The estimated inputs as well as the performance of the influence functions are calculated.

• Journal of the Korean Statistical Society
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• v.17 no.1
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• pp.9-23
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• 1988

The classicla theory of statistical calibration assumes that the standard measurement is exact. From a realistic point of view, however, this assumption needs to be relaxed so that more meaningful calibration procedures may be developed. This paper presents a model which explicitly considers errors in both standard and nonstandard measurements. Under the assumption that replicated observations are available in the calibration experiment, three estimation techniques (ordinary least squares, grouping least squares, and maximum likelihood estimation) combined with two prediction methods (direct and inverse prediction) are compared in terms of the asymptotic mean square error of prediction.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.204-212
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• 2014

The purpose of this paper is to investigate the effects of calibration rounds on the statistical distribution of the muzzle velocity in acceptance test of propelling charge. It is shown that the normal distribution fits best among statistical distributions from goodness-of fit test. The 3p-Weibull distribution is also acceptable because the shape of the probability density function curve is similar to that of normal distribution and it also has near zero skewness value. Muzzle velocities of test rounds uncompensated by calibration rounds showed high variation and had comparatively higher skewness. Because the skewness of normal distribution is defined to be zero, calibration rounds make the normality of data higher.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.219-234
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• 1993

A measuring instrument must be calibrated for accurate inferences of an unknown quantity. Bayesian calibration designs with respect to squared error loss based on a linear model are discussed in Kim and Barlow (1992). In this paper, we consider approximations of the optimal calibration designs using the idea of Gaussian inflence diagrams. The approximation is evaluated by means of numerical calculations, where it is compared with the exact values from the numerical integration.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.85-90
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• 2005

This paper proposes the calibration procedure for stratified Warner's randomized response model, which suggested by Kim and Warde (2004). It is shown that the proposed calibration estimator is more efficient than the Kim and Warde's model.

• Communications for Statistical Applications and Methods
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• v.15 no.4
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• pp.597-603
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• 2008

In this paper, we propose the calibration procedure for the valiance reduction of the stratified Warner's randomized response estimators, which suggested by Hong et al. (1994) and Kim and Warde (2004), using auxiliary information at the population level. It is shown that the proposed calibration estimators are more efficient than the ordinary Warner's estimators.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.61-70
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• 2013

This paper presents the response calibration method based on quality control range, which is established from the concept and method of statistical quality control for natural frequency ratio and response ratio. To this end, statistical analysis including descriptive statistics analysis, normality test, ANOVA were performed for response characteristics obtained from loading tests and structural analysis for more than hundred and thirty well-conditioned bridges. Suggested method is based on real structural integrity evaluation case studies and statistical quality control approach, in this respect it is expected to provide scientific criteria and systematic procedure for response calibration and load carrying capacity assessment.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.227-235
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• 1993

Calibration relates the estimation of independent variable which rquires more effort or expense than dependent variable does. It would be provided with high accuracy because a little change of the result of independent variable cn cause a serious effect to the human being. Usual statistical analysis assumes the normality of error distribution or linearity of data. It is desirable to analyze the data without those assumptions for the accuracy of the calibration. In this paper, we calibrated the data nonparametrically without those assumptions and derived confidence interval estimate for the independent variable. As a method, we used kernel method which is popular in modern statistical branch. We derived bootstrap confidence interval estimate from the bootstrap confidence band.