• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.537-549
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• 1995

In this article, we propose a class of weighted estimators for the excess risk in additive risk model with a binary covariate. The proposed estimator is consistent and asymptotically normal. When the assumed model is inappropriate, however, the estimators with different weights converge to nonidentical constants. This fact enables us to develop a goodness-of-fit test for the excess assumption by comparing estimators with diffrent weights. It is shown that the proposed test converges in distribution to normal with mean zero and is consistent under the model misspecifications. Furthermore, the finite-sample properties of the proposed test procedure are investigated and two examples using real data are presented.

• The Journal of Advanced Prosthodontics
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• v.13 no.5
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• pp.333-342
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• 2021

PURPOSE. To evaluate the impact of five different tooth preparation designs on the marginal and internal fit discrepancies of cobalt-chromium (CoCr) crowns produced by computer-aided designing (CAD) and selective laser melting (SLM) processes. MATERIALS AND METHODS. Five preparation data were constructed, after which design crowns were obtained. Actual crowns were fabricated using an SLM process. After the data of actual crowns were obtained with structural light scanning, intaglio surfaces of the design crown and actual crown were virtually superimposed on the preparation. The fit-discrepancies were displayed with colors, while the root means square was calculated and analyzed with one-way analysis of variance (ANOVA), Tukey's test or Kruskal-Wallis test (α = .05). RESULTS. The marginal or internal color-coded images in the five design groups were not identical. The shoulder-lip and sharp line angle groups in the CAD or SLM process had larger marginal or internal fit discrepancies compared to other groups (P < .05). In the CAD process, the mean marginal and internal fit discrepancies were 10.0 to 24.2 ㎛ and 29.6 to 31.4 ㎛, respectively. After the CAD and SLM processes, the mean marginal and internal fit discrepancies were 18.4 to 40.9 ㎛ and 39.1 to 47.1 ㎛, respectively. The SLM process itself resulted in a positive increase of the marginal (6.0 - 16.7 ㎛) and internal (9.0 - 15.7 ㎛) fit discrepancies. CONCLUSION. The CAD and SLM processes affected the fit of CoCr crowns and varied based on the preparation designs. Typically, the shoulder-lip and sharp line angle designs had a more significant effect on crown fit. However, the differences between the design groups were relatively small, especially when compared to fit discrepancies observed clinically.

• The Journal of Advanced Prosthodontics
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• v.2 no.3
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• pp.102-105
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• 2010

PURPOSE. The aims of this study were to suggest a method of fabrication of the record base using a light-polymerized resin by applying the two-phase fabrication method for the improvement of the fit of the record base and to compare the degree of fit according to the separation site. MATERIALS AND METHODS. In the edentulous cast of maxilla, four test groups were considered. In the first, second, third, and fourth test groups (n = 12 in each group) the separation was done at 0, 5, 10, and 15 mm, respectively below the alveolar crest along the palatal plane. For the control group, the record base was made without separating the two sections. The light-body silicone material was injected into the fitting surface of the record base. It was then placed onto the cast and finger pressure was applied to stabilize it in a seated position followed by immediate placement onto the universal test device. Finally, the mass of the impression material was measured after it was removed. ANOVA was performed using the SAS program. For the post-hoc test, the Wilcoxon Rank-Sum test and the Tukey-Kramer HSD test were performed ($\alpha$ = 0.05). RESULTS. The control group and Group 3, 4 showed significant differences. The Group 3 and 4 showed significantly smaller inside gaps than the control group which was not made with the two-phase fabrication method. CONCLUSION. The two-stage polymerized technique can improve the fit of the denture base particularly when the separation was made at 10 to 15 mm from the alveolar crest.

• Journal of the Korea Fashion and Costume Design Association
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• v.12 no.4
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• pp.75-88
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• 2010

The objective of this study is to investigate the fit preference tendency for ready-to-wears(jackets, skirts and slacks) of adult women and to find out the respective differences by the age range and the obesity level. The study method was the questionnaire survey with the subjects of 295 women of 20 up to 59 years of age. The questionnaire is composed of fit preference tendency, physical measurements, age, and occupation. For the data analysis, SPSS 18.0 program was used, and descriptive statistics, Crosstabs, ANOVA, Duncan's test, t-test and multiple regression were conducted. The findings were as follows. 1. Regarding the fit preferred for each part of jackets, skirts, and slacks, among ready-to-wears, the 'thing with some extra width' in every part was most favored, followed by the 'thing fitting perfectly.' 2. The differences were found in the fit preference tendency by the age of adult women. The fit preference tendency was higher among those in their 20's than among those of the other age range. 3. The differences were also found in the fit preference tendency by the obesity level of adult women. The fit preference tendency was high in the order of the emaciation, normalcy, and obesity types. 4. For all of three items, age and body type or body type influenced the preference by the fit level. As the age was higher and the body type was fatter, those items with some flexibility were preferred.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.645-660
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• 2001

In this paper we propose a goodness-of-fit test statistic for testing the (null) parametric model versus the (alternative) nonparametric model. Most of existing nonparametric test statistics are based on the residuals which are obtained by regressing the data to a parametric model. Our test is based on the bootstrap estimator of the probability that the smoothing parameter estimator is infinite when fitting residuals to cubic smoothing spline. Power performance of this test is investigated and is compared with many other tests. Illustrative examples based on real data sets are given.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.483-497
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• 2001

When one fits a parametric density function to a data set, it is usually advisable to test the goodness of the postulated model. In this paper we study the nonparametric tests for testing the null hypothesis against general alternatives, when the null hypothesis specifies the density function up to unknown parameters. We modify the test statistic which was proposed by the first author and his colleagues. Asymptotic distribution of the modified statistic is derived and its performance is compared with some other tests through simulation.

• International Journal of Reliability and Applications
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• v.7 no.2
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• pp.141-153
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• 2006

In this paper, we present the U-Statistic test for testing exponentiality against new renewal better than used (NRBU) based on a goodness of fit approach. Selected critical values are tabulated for sample sizes n=5(1)30(10)50. The asymptotic Pitman relative efficiency relative to (NRBU) test given in the work of Mahmoud et all (2003) is studied. The power estimates of this test for some commonly used life distributions in reliability are also calculated. Some of real examples are given to elucidate the use of the proposed test statistic in the reliability analysis. The problem in case of right censored data is also handled.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.909-918
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• 1999

Arizono and Ohta(1989) studied goodness of fit test of normality using the entropy estimator proposed by Vasicek (1976) Recently van Es(1992) and Correa(1995) proposed an estimator of entropy. In this paper we propose goodness of fit test statistics for normality based on Vasicek ven Es and Correa. And we compare the power of the proposed test statistics with Kolmogorov-Smirnov Kuiper Cramer von Mises Watson Anderson-Darling and Finkelstein and Schefer statistics.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.125-134
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• 2014

Kullback-Leibler (KL) information is a measure of discrepancy between two probability density functions. However, several nonparametric density function estimators have been considered in estimating KL information because KL information is not well-defined on the empirical distribution function. In this paper, we consider the KL information of the equilibrium distribution function, which is well defined on the empirical distribution function (EDF), and propose an EDF-based goodness of fit test statistic. We evaluate the performance of the proposed test statistic for an exponential distribution with Monte Carlo simulation. We also extend the discussion to the censored case.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.313-321
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• 2004

We consider the problem of testing cell probabilities in sparse multinomial data. Aerts et al. (2000) presented T=${{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2$ as a test statistic with the local least square polynomial estimator ${{p}_{i}}^{*}$, and derived its asymptotic distribution. The local least square estimator may produce negative estimates for cell probabilities. The local maximum likelihood polynomial estimator ${{\hat{p}}_{i}}$, however, guarantees positive estimates for cell probabilities and has the same asymptotic performance as the local least square estimator (Baek and Park, 2003). When there are cell probabilities with relatively much different sizes, the same contribution of the difference between the estimator and the hypothetical probability at each cell in their test statistic would not be proper to measure the total goodness-of-fit. We consider a Pearson type of goodness-of-fit test statistic, $T_1={{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2/p_{i}$ instead, and show it follows an asymptotic normal distribution. Also we investigate the asymptotic normality of $T_2={{\Sigma}_{i=1}}^{k}{[{p_i}^{*}-E{(p_{i}}^{*})]^2/p_{i}$ where the minimum expected cell frequency is very small.