• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2012.04a
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• pp.190-193
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• 2012

The tools that classify the severity of patients based on the prediction of mortality include APACHE, SAPS, and MPM. Theses tools rely crucially on the evaluation of patients' general clinical status on the first date of their admission to ICU. Nursing activities are one of the most crucial factors influencing on the quality of treatment that patients receive and one of the contributing factors for their prognosis and safety. The purpose of this study was to identify the goodness-of-fit of CPSCS of critical patient severity classification system(CPSCS) and Glasgow coma scale(GCS) and the clinical usefulness of its death rate prediction. Data were collected from the medical records of 187 neurological patients who were admitted to the ICU of C University Hospital. The data were analyzed through $x^2$ test, t-test, Mann-Whitney, Kruskal-Wallis, goodness-of-fit test, and ROC curve. In accordance with patients' general and clinical characteristics, patient mortality turned out to be statistically different depending on ICU stay, endotracheal intubation, central venous catheter, and severity by CPSCS. Homer-Lemeshow goodness-of-fit tests were CPSCS and GCS and the results of the discrimination test using the ROC curve were $CPSCS_0$,.734, $GCS_0$,.583, $CPSCS_{24}$,.734, $GCS_{24}$,.612, $CPSCS_{48}$,.591, $GCS_{48}$,.646, $CPSCS_{72}$,.622, and $GCS_{72}$,.623. Logistic regression analysis showed that each point on the CPSCS score signifies1.034 higher likelihood of dying. Applied to neurologically ill patients, early CPSCS scores can be regarded as a useful tool.

• Journal of the Korean Statistical Society
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• v.29 no.2
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• pp.201-217
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• 2000

The method of generalized estimating equations (GEE) has become very popular for the analysis of longitudinal data. We extend this work to the use of M-estimators; the resultant regression estimates are robust to heavy tailed errors and to outliers. The proposed method does not require correct specification of the dependence structure between observation, and allows for heterogeneity of the error. However, an estimate of the dependence structure may be incorporated, and if it is correct this guarantees a higher efficiency for the regression estimators. A goodness-of-fit test for checking the adequacy of the assumed M-estimation regression model is also provided. Simulation studies are conducted to show the finite-sample performance of the new methods. The proposed methods are applied to a real-life data set.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1271-1284
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• 2011

The entropy-based test of fit for the inverse Gaussian distribution presented by Mudholkar and Tian(2002) can only be applied to the composite hypothesis that a sample is drawn from an inverse Gaussian distribution with both the location and scale parameters unknown. In application, however, a researcher may want a test of fit either for an inverse Gaussian distribution with one parameter known or for an inverse Gaussian distribution with both the two partameters known. In this paper, we introduce tests of fit for the inverse Gaussian distribution based on the Kullback-Leibler information as an extension of the entropy-based test. A window size should be chosen to implement the proposed tests. By means of Monte Carlo simulations, window sizes are determined for a wide range of sample sizes and the corresponding critical values of the test statistics are estimated. The results of power analysis for various alternatives report that the Kullback-Leibler information-based goodness-of-fit tests have good power.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.903-914
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• 2014

The inverse Weibull distribution has been proposed as a model in the analysis of life testing data. Also, inverse Weibull distribution has been recently derived as a suitable model to describe degradation phenomena of mechanical components such as the dynamic components (pistons, crankshaft, etc.) of diesel engines. In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and the shape parameter in the inverse Weibull distribution under multiply type-II censoring. We also develop four modified empirical distribution function (EDF) type tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples. We also propose modified normalized sample Lorenz curve plot and new test statistic.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.877-887
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• 2002

In this paper, behaviors and properties of p-values for goodness-of-fit test are investigated. With some findings on the p-values, we consider some applications to determine sample size of a survey research using the regression equation based on a pilot study data. Regression equations are obtained by the well-known least squared method, and we find that regression lines could be formulated with only two data points, alternatively. For further studies, this works might be extended to t distributions for testing hypotheses about population mean in order to determine sample size of a prospective study. Also similar arguments could be explored for F test statistics.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.259-268
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• 2006

For Type-II censored sample, we propose three modified entropy estimators based on the Vasieck's estimator, van Es' estimator, and Correa's estimator. We also propose the goodness-of-fit tests of the Weibull distribution based on the modified entropy estimators. We simulate the mean squared errors (MSE) of the proposed entropy estimators and the powers of the proposed tests. We also compare the proposed tests with the modified Kolmogorov-Smirnov and Cramer-von-Mises tests which were proposed by Kang et al. (2003).

• The Korean Journal of Applied Statistics
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• v.4 no.2
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• pp.157-170
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• 1991

This article is concerned with the goodness - of - fit test for exponentiality when both the scale and location parameters are unknown. A test procedure based on the $L_1$-norm of discrepancy between the cumulative distribution function and the empirical distribution function is proposed, and the critical values of the test statistic are obtained by Monte Carlo simulations. Also the null distributions of the proposed test statistic are presented for small sample sizes. The power of tests under certain alternative distributions is investigated to compare the proposed test statistic with the well-known EDF test statistics. Our Monte Carlo power studies reveal that the proposed test statistic has good power properties, for moderate-to-large sample sizes, in comparison to other statistics although it is a conservative test.

• Water for future
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• v.7 no.2
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• pp.107-111
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• 1974

Annual runoff in the Nakdong river basin has been analyzed to find the probability functions of best fit to distribution of historical annual runoff. The results obtained are as follows; (1) Log-normal 3-parameter disrtibution is believed as the probability function of best fit to historical distribution (2) Log-normal 3-parameter disrtibution is believed as the best fit probability function among Log-normal dist-ributions. (3) In the test of goodness of fit, $x^2-test$ shows that probability of $x^2-valus$ in Log-normal 3-parameter distribution is nearly more than 90%. But in the Simirnov-Kolmogorov test, hypotheses for the probability distributions cannot be rejected at significance level 5% & 1%. (4) Among 7 gauging stations, Dongchon & Koryung-Bridge's records show lower fitness to the theoretical probability functions than other 5 gauging station's

• 재활복지
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• v.21 no.2
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• pp.169-190
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• 2017

The purpose of this study was to investigate item goodness-of-fit of Scale, Rasch rating scale model was applied to 5 dimensions 24 items of the Test of Performance Strategies (TOPS) in a sample of athletes with physical disabilities (n=215). An assumption to test Rasch Model, which is satisfaction of unidimensionality, is regarded through PCAR test, and WINSTEPS 3.65 program is used to test the goodness-of-fit of items. The results of this study were: First, 3-point rating category was appropriate for the TOPS instead of the existing 5-point rating category. Second, as a result of analyzing the goodness-of-fit of the items, 21 items of the TOPS were suitable, but 3 items were not. Third, the item reliability of person separation of the TOPS was acceptable, but the person reliability of item separation was not suitable and it was necessary to adjust the item order considering the difficulty level of the items. Fourth, as a result of comparing the individual attribute score and the difficulty level through the Item-Person Map, the distribution of the item difficulty distribution was shown to be biased in some factors compared to the personal attribute score distribution.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.289-302
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• 1993

A goodness-of-fit test for the two-parameter exponential distribution, for use with the singly Type I and Type II right censored samples, is proposed. The test statistic is based on the $L_1$-norm of discrepancy between the cumulative distribution function and the empirical distribution function. To deal with the unknown parameters problem, the K- transformation is considered and modified to be applied to the censored samples. Rosenblatt's transformation is extended to the cases of Type I and Type II censored samples, in order to transform the censored samples into the complete ones. The critial values of the test statistic are obtained by Monte Carlo simulations for some finite sample sizes. The power studies are conducted to compare the proposed test with the Pettitt(1977) test for exponentiality with censored samples. It appears that the proposed test has relatively good power properties for moderate and large sample sizes.