• Title/Summary/Keyword: goodness of fit test

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Bond Models for GFRP Rebar Embedded in Concrete (GFRP 보강근과 콘크리트 사이의 부착모델에 관한 고찰)

  • You, Young-Jun;Park, Ji-Sun;Park, Young-Hwan;Kim, Hyeong-Yeol
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.10 no.3
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    • pp.143-151
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    • 2006
  • This paper presents the comparison of the goodness-of-fit test of analytical bond models between concrete and steel or GFRP reinforcements. Bond test specimens were prepared in accordance with the CSA codes and the rebars used in the test were steel and two types of commercial GFRP rebar products. Using the test data, a bond model was proposed, and comparison of goodness-of-fit test for existing bond models and proposed bond model was carried out by the least squares method. The result indicates that the proposed bond model has better goodness-of-fit test than the existing ones.

Testing Goodness of Fit in Nonparametric Function Estimation Techniques for Proportional Hazards Model

  • Kim, Jong-Tae
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.435-444
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    • 1997
  • The objective of this study is to investigate the problem of goodness of fit testing based on nonparametric function estimation techniques for the random censorship model. The small and large sample properties of the proposed test, $E_{mn}$, were investigated and it is shown that under the proportional hazard model $E_{mn}$ has higher power compared to the powers of the Kolmogorov -Smirnov, Kuiper, Cramer-von Mises, and analogue of the Cramer-von Mises type test statistic.

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Testing Goodness-of-Fit for No Effect Models

  • Sungho Lee;Jongtae Kim;GyoungAe Moon
    • Communications for Statistical Applications and Methods
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    • v.5 no.3
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    • pp.935-944
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    • 1998
  • This paper investigates the problem of goodness of fit tests for no effect model. The proposed test statistic $Z_{mn}$ is obtained by multiplying constant on the model free curve estimation techniques. The small and large sample properties of$Z_{mn}$ are investigated and the good results of power studies for the proposed test are illustrated.

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Goodness-of-fit Test for the Extreme Value Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok;Cho, Young-Seuk;Han, Jun-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1441-1448
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    • 2008
  • We propose the modified quantile-quantile (Q-Q) plot using the approximate maximum likelihood estimators and the modified normalized sample Lorenz curve (NSLC) plot for the extreme value distribution based on multiply Type-II censored samples. Using two example data sets, we picture the modified Q-Q plot and the modified NSLC plot.

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Goodness-of-fit tests for randomly censored Weibull distributions with estimated parameters

  • Kim, Namhyun
    • Communications for Statistical Applications and Methods
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    • v.24 no.5
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    • pp.519-531
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    • 2017
  • We consider goodness-of-fit test statistics for Weibull distributions when data are randomly censored and the parameters are unknown. Koziol and Green (Biometrika, 63, 465-474, 1976) proposed the $Cram\acute{e}r$-von Mises statistic's randomly censored version for a simple hypothesis based on the Kaplan-Meier product limit of the distribution function. We apply their idea to the other statistics based on the empirical distribution function such as the Kolmogorov-Smirnov and Liao and Shimokawa (Journal of Statistical Computation and Simulation, 64, 23-48, 1999) statistics. The latter is a hybrid of the Kolmogorov-Smirnov, $Cram\acute{e}r$-von Mises, and Anderson-Darling statistics. These statistics as well as the Koziol-Green statistic are considered as test statistics for randomly censored Weibull distributions with estimated parameters. The null distributions depend on the estimation method since the test statistics are not distribution free when the parameters are estimated. Maximum likelihood estimation and the graphical plotting method with the least squares are considered for parameter estimation. A simulation study enables the Liao-Shimokawa statistic to show a relatively high power in many alternatives; however, the null distribution heavily depends on the parameter estimation. Meanwhile, the Koziol-Green statistic provides moderate power and the null distribution does not significantly change upon the parameter estimation.

Validity and Reliability of Korean Version of the Revised Stress Appraisal Measure (RSAM) (한국어판 수정된 스트레스 평가 도구(Revised Stress Appraisal Measure)의 타당도와 신뢰도)

  • Kim, Jeong Sun;Kim, Kye-Ha;Kang, Hyuncheol
    • The Journal of the Korea Contents Association
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    • v.15 no.3
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    • pp.290-302
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    • 2015
  • The study purpose was to test the validity and reliability of the Korean version of the Revised Stress Appraisal Measure (RSAM) to assess stress appraisal in undergraduate students. Internal consistency reliability, construct and criterion validity were calculated using IBM SPSS Statistics 21 and AMOS 21 program. Survey data were collected from a convenience sample of 296 undergraduate students enrolled in five universities in G city and C area, South Korea. The Korean version of RSAM categorized into 5 factors explaining 68.4% of the total variance. The model of five subscales was validated by confirmatory factor analysis (p<.001, Goodness of Fit Index, Adjusted Goodness of Fit Index, Normed Fit Index, Comparative Fit Index >.08, Root Mean Square Error of Approximation=.056). In criterion validity, the scores for the scale were significantly correlated with the Perceived Stress Scale-Korean. Cronbach's alpha coefficient for the 19 items was .73~.89. The Korean RSAM showed satisfactory construct and criterion validity and reliability. Thus it may be an appropriate instrument for measuring stress appraisal in Korean university students.

Turkish Version of the Perceived Future Decent Work Securement Scale: Validity and Reliability for Nursing Students

  • Oznur Ispir Demir;Betul Sonmez;Duygu Gul;Sergul Duygulu
    • Safety and Health at Work
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    • v.14 no.3
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    • pp.332-339
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    • 2023
  • Background: The aim of the study was to test the validity and reliability of the Perceived Future Decent Work Securement Scale for Turkish nursing students. Methods: A cross-sectional, methodological study design was used. The study was carried out at three nursing undergraduate programs in Turkey during the academic year of 2020-2021 with 336 senior nursing students. Language validity and content validity analyses were performed for the scale adaptation, followed by confirmatory factor analysis (CFA) for construct validity. The reliability of the scale was determined using the test-retest and Cronbach's alpha internal consistency coefficient. Results: The scale-content validity index score was 0.988. In CFA, all goodness-of-fit indices verified the acceptable fit of the model; its root mean square error of approximation was 0.076; the normed fit index was 0.909; the standardized mean square residual was 0.097; the relative fit index was 0.881; the goodness-of-fit index was 0.915; the adjusted goodness-of-fit index was 0.872 and χ2/df = 2.932. The overall reliability was α = 0.86. The item-total correlations of the scale were above the acceptable level, and the test-retest analysis had a high correlation. The access to healthcare (14.68, SD 3.53) obtained the highest average score, and the adequate compensation (8.52, SD 3.76) was the lowest rated by the senior nursing students. Conclusion: The Perceived Future Decent Work Securement Scale is a valid and reliable scale to assess nursing students' future decent work securement.

Comparison of Parameter Estimation Methods in the Analysis of Multivariate Categorical Data with Logit Models

  • Song, Hae-Hiang
    • Journal of the Korean Statistical Society
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    • v.12 no.1
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    • pp.24-35
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    • 1983
  • In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

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A goodness-of-fit test based on Martinale residuals for the additive risk model (마팅게일잔차에 기초한 가산위험모형의 적합도검정법)

  • 김진흠;이승연
    • The Korean Journal of Applied Statistics
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    • v.9 no.1
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    • pp.75-89
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    • 1996
  • This paper proposes a goodness-of-fit test for checking the adequacy of the additive risk model with a binary covariate. The test statistic is based on martingale residuals, which is the extended form of Wei(1984)'s test. The proposed test is shown to be consistent and asymptotically normally distributed under the regularity conditions. Furthermore, the test procedure is illustrated with two set of real data and the results are discussed.

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Study on Rainfall Regional Frequency Analysis (강우 지역빈도해석의 적용성 연구)

  • Shin Hong Joon;Nam Woo Sung;Heo Jun Haeng;Kim Kyung Duk
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.593-598
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    • 2005
  • At-site analysis is not appropriate if the record length is shorter than target return period T. If the record length is longer than 27 years, then at-site analysis may be sufficient(Institute of Hydrology, 1999). However, in such a case, regional frequency analysis is recommended for purpose of comparison. Record lengths of annual maximum rainfall data in Korea are usually shorter than 50 years. It is therefore essential to apply regional frequency analysis for estimating rainfall quantiles of more than 100 years return period. In this research, regional rainfall frequency analysis is performed for hourly rainfall data of South Korea. Homogeneous regions are idntified by clusgter analysis which is a standard method of statistical multivariate analysis for dividing a data set into groups. An appropriate distribution is chosen by goodness-of-fit test. GLO is found to be an appropriate distribution as a result of goodness-of-fit measure (Hosking & Wallis, 1997). Simulation experiments are performed to check the performance of frequency analysis techniques. The effects of discordant sites on quantiles are considered.

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