• Investigative Magnetic Resonance Imaging
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• v.20 no.4
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• pp.207-214
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• 2016

Purpose: The purpose of this study was to investigate the effect of the number of measurement points on the calculation of transverse relaxation time (T2) with a focus on muscle T2. Materials and Methods: This study assumed that muscle T2 was comprised of a single component. Two phantom types were measured, 1 each for long ("phantom") and short T2 ("polyvinyl alcohol gel"). Right calf muscle T2 measurements were conducted in 9 healthy male volunteers using multiple-spin-echo magnetic resonance imaging. For phantoms and muscle (medial gastrocnemius), 5 regions of interests were selected. All region of interest values were expressed as the mean ${\pm}$ standard deviation. The T2 effective signal-ratio characteristics were used as an index to evaluate the magnetic resonance image quality for the calculation of T2 from T2-weighted images. The T2 accuracy was evaluated to determine the T2 reproducibility and the goodness-of-fit from the probability Q. Results: For the phantom and polyvinyl alcohol gel, the standard deviation of the magnetic resonance image signal at each echo time was narrow and mono-exponential, which caused large variations in the muscle T2 decay curves. The T2 effective signal-ratio change varied with T2, with the greatest decreases apparent for a short T2. There were no significant differences in T2 reproducibility when > 3 measurement points were used. There were no significant differences in goodness-of-fit when > 6 measurement points were used. Although the measurement point evaluations were stable when > 3 measurement points were used, calculation of T2 using 4 measurement points had the highest accuracy according to the goodness-of-fit. Even if the number of measurement points was increased, there was little improvement in the probability Q. Conclusion: Four measurement points gave excellent reproducibility and goodness-of-fit when muscle T2 was considered mono-exponential.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1057-1065
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• 2010

In this paper we discuss some cautionary notes in using the Pearson chi-squared test statistic for the goodness-of-fit of the ordinal response model. If a model includes continuous type explanatory variables, the resulting table from the t of a model is not a regular one in the sense that the cell boundaries are not fixed but randomly determined by some other criteria. The chi-squared statistic from this kind of table does not have a limiting chi-square distribution in general and we need to be very cautious of the use of a chi-squared type goodness-of-t test. We also study the limiting distribution of the chi-squared type statistic for testing the goodness-of-t of cumulative logit models with ordinal responses. The regularity conditions necessary to the limiting distribution will be reformulated in the framework of the cumulative logit model by modifying those of Moore and Spruill (1975). Due to the complex limiting distribution, a parametric bootstrap testing procedure is a good alternative and we explained the suggested method through a practical example of an ordinal response dataset.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.587-592
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• 2009

The most frequent use of the chi-square distribution is in the area of goodness-of-t of a distribution. The likelihood ratio test is a commonly used test statistic as the maximum likelihood estimate in statistical inferences. The recently revised versions of the likelihood ratio test statistics are used in estimating the parameter in the chi-square distribution. The estimates are compared with the commonly used method of moments and the maximum likelihood estimate.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.261-276
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• 1997

In the context of binary response regression, the problem of constructing Bayesian goodness-of-link test for testing logit link versus probit link is considered. Based upon the well known facts that cdf of logistic variate .approx. cdf of $t_{8}$/.634 and, as .nu. .to. .infty., cdf of $t_{\nu}$ approximates to that of N(0,1), Bayes factor is derived as a test criterion. A synthesis of the Gibbs sampling and a marginal likelihood estimation scheme is also proposed to compute the Bayes factor. Performance of the test is investigated via Monte Carlo study. The new test is also illustrated with an empirical data example.e.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.303-311
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• 2003

We consider the problem of testing cell probabilities in sparse multinomial data. Aerts, et al.(2000) presented $T_1=\sum\limits_{i=1}^k(\hat{p}_i-p_i)^2$ as a test statistic with the local polynomial estimator $(\hat{p}_i$, and showed its asymptotic distribution. 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, $T=\sum\limits_{i=1}^k(\hat{p}_i-p_i)^2/p_i$ instead, and show it follows an asymptotic normal distribution.

• International Journal of Reliability and Applications
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• v.7 no.1
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• pp.1-11
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• 2006

The better mean residual life at $t_0\;(BMRL-t_0)$ class of life distribution is introduced by Kulasekara and Park (1987). They proved that the $BMRL-t_0$ class contains the DMRL class, but it is a proper subclass of the NBUE class. In this paper we develop a new family of tests for testing exponentiality against the $BMRL-t_0\;(WMRL-t_0)$ alternatives based on the goodness of fit approach. It is shown that the suggested test is better than the one introduced by Kulasekara and Park (1987) in the sense of Pitman asymptotic efficiency values.

• Korean Journal of Childcare and Education
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• v.13 no.1
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• pp.43-63
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• 2017

Objective: The goal of this study was to clarify the differences in children's child care center adjustment depending on child-mother's goodness of fit. Methods: A total of 478 subjects, 239 dyads of 3 and 4 year old children and their mothers and 16 teachers participated in this study. The instruments used in this study were the DOTS-R, EAS Scale and PAQ. The collected data were analyzed using a t-test, Anova, and regression with the SPSS. Results: First, mother's demand was significantly different only with regard to the income level. Second, mother's temperament and mother's demand were positively correlated and the mother's demand was influenced by the mother's temperament. Third, mother's demand according to children's gender was indicated to differ significantly. Fourth, children's temperament and mother's demand were positively correlated and mother's demand was influenced by children's temperament. Finally, ego strength according to active and adoptive temperaments in child-mother's goodness of fit had significant differences. In addition, prosocial behavior according to regular temperament of child-mother's goodness of fit was indicated to have a significant difference. Conclusion/Implications: This study suggests that it is important for mothers to understand and appropriately demand the temperament of the children in the adaptation of the child care center.

• The Journal of Korean Philosophical History
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• no.28
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• pp.417-445
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• 2010

There are a few changes about Wangshouren's main tenet during the process of giving lectures. because of the reason that Wangshouren give lectures changed to different disciples, so every student had his different opinion and comprehension do Wangshouren's learning, which is the main reason that Wangshouren's disciples had occurred a difference. In the thinking field of later-Ming, there had occurred a furious argument surrounding the problem of "the Heart is no Goodness and Badness or not", and how to cure the harm of the Xinxue also had become a key issue to the two sides of argument. The donglin school that Guxiancheng was its delegates made a contest with the Xinxue's scholars that Zhourudeng and Guanzhidao were that delegates, which evolved surrounding that issue that "the nature is Good" and "the Heart no Goodness and Badness". In these arguments, the two sides often persist on their own opinions, but hadn't a right understanding for Wangshouren's original meaning. Liujishan and Huanglizhou thought that the meaning of the words "the Heart no Goodness and Badness" was that the Heart have no the intention of Goodness and Badness, not that the Nature was no Goodness and no Badness. So that the opinion of "the Heart no Goodness and Badness" was not the main idea of Wangshouren. Wangji hadn't got the whole meaning of the Four Sentences. Liujishan and Huanglizhou wanted to make a new explaination to Wangshouren's ideas according to literatures and theory.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1497-1501
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• 2013

Cumulative residual Kullback-Leibler (CRKL) information is well defined on the empirical distribution function (EDF) and allows us to construct a EDF-based goodness of t test statistic. However, we need to consider a scaled CRKL because CRKL is not scale invariant. In this paper, we consider several criterions for estimating the scale parameter in the scale CRKL and compare the performances of the estimated CRKL in terms of both power and unbiasedness.