• Title/Summary/Keyword: Chi-square Test

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Robust Scene Change Detection Algorithm for Flashlight (플래시라이트에 강건한 장면전환 검출 알고리즘)

  • Ko, Kyong-Cheol;Choi, Hyung-Il;Rhee, Yang-Weon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.6 s.312
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    • pp.83-91
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    • 2006
  • Flashlights in video has many problem to detect the scene change because of high difference values from successive frames. In this paper propose the reliable scene change detection algorithms by extracting the flashlights. This paper proposes a robust scene change detection technique that uses the weighted chi-square test and the automated threshold-decision algorithms. The weighted chi-square test can subdivide the difference values of individual color channels by calculating the color intensities according to NTSC standard, and it can detect the scene change by joining the weighted color intensities to the predefined chi-square test which emphasize the comparative color difference values. The automated threshold-decision algorithm uses the difference values of frame-to-frame that was obtained by the weighted chi-square test. At first, The Average of total difference values is calculated and then, another average value is calculated using the previous average value from the difference values, finally the most appropriate mid-average value is searched and considered the threshold value. Experimental results show that the proposed algorithms are effective and outperform the previous approaches.

Performance of APACHE IV in Medical Intensive Care Unit Patients: Comparisons with APACHE II, SAPS 3, and MPM0 III

  • Ko, Mihye;Shim, Miyoung;Lee, Sang-Min;Kim, Yujin;Yoon, Soyoung
    • Acute and Critical Care
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    • v.33 no.4
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    • pp.216-221
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    • 2018
  • Background: In this study, we analyze the performance of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS) 3, and Mortality Probability Model $(MPM)_0$ III in order to determine which system best implements data related to the severity of medical intensive care unit (ICU) patients. Methods: The present study was a retrospective investigation analyzing the discrimination and calibration of APACHE II, APACHE IV, SAPS 3, and $MPM_0$ III when used to evaluate medical ICU patients. Data were collected for 788 patients admitted to the ICU from January 1, 2015 to December 31, 2015. All patients were aged 18 years or older with ICU stays of at least 24 hours. The discrimination abilities of the three systems were evaluated using c-statistics, while calibration was evaluated by the Hosmer-Lemeshow test. A severity correction model was created using logistics regression analysis. Results: For the APACHE IV, SAPS 3, $MPM_0$ III, and APACHE II systems, the area under the receiver operating characteristic curves was 0.745 for APACHE IV, resulting in the highest discrimination among all four scoring systems. The value was 0.729 for APACHE II, 0.700 for SAP 3, and 0.670 for $MPM_0$ III. All severity scoring systems showed good calibrations: APACHE II (chi-square, 12.540; P=0.129), APACHE IV (chi-square, 6.959; P=0.541), SAPS 3 (chi-square, 9.290; P=0.318), and $MPM_0$ III (chi-square, 11.128; P=0.133). Conclusions: APACHE IV provided the best discrimination and calibration abilities and was useful for quality assessment and predicting mortality in medical ICU patients.

Jackknifed Cochran-Mantel-Haenszel Test for Conditional Independence in Sparse $2\tims2\tims$K Tables

  • Jeong, Kwang-Mo
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.51-63
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    • 2001
  • We are interested in the conditional independence in sparse $2\tims2\tims$K tables with very rare cell counts. The most popular test is Cochran-Mantel-Haenszel statistic when sample sizes are moderately large enough to guarantee the chi-square approximation. We will consider jackknifing the CMH test and also suggest an approximate normal distribution for the standardized jackknifed CMH statistic. The main focus of this paper is to improve the chi-squared approximation to the CMH test by using the asymptotic normality of the jackknifed CMH test when sample sizes are very sparse but K and N$\infty$. The performance of the proposed jackknifed test, in the sense of significance level control and power, will be compared with that of the CMH test through a Monte Carlo study.

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Effects of Group Tai Chi Exercise Prograam on Body Mass Index(BMI), Positive and Negative Psychiatric Symptoms in Patient with Schizophrenia (타이치 운동프로그램이 정신분열병 환자의 신체질량지수와 양성 및 음성 정신 증상에 미치는 효과)

  • Kwon, Yun-Hee;Kwag, Oh-Gye
    • The Korean Journal of Rehabilitation Nursing
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    • v.14 no.2
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    • pp.129-135
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    • 2011
  • Purpose: This study was done to examine the effects of Tai Chi exercise program on BMI, positive and negative psychiatric symptoms in patient with schizophrenia. Methods: The participants were patient with schizophrenia in S psychiatric hospital in D city. Twenty five patients were assigned to experimental group, and 26 patients were assigned to control group. Data were collected from May 9, to July 8, 2011. The Tai Chi exercise program was conducted with a duration of 60 minutes, 2 times a week for 8 weeks (a total 8 times). Measures were BMI, positive and negative psychiatric symptoms. Data were analyzed using descriptive statistics, chi-square test and t-test with SPSS/WIN 19.0 version. Result: The experimental group received Tai Chi exercise program had a significant changes in BMI, positive and negative psychiatric symptoms. Conclusion: The results of this study indicate that Tai Chi exercise program is an effective intervention program to improve the BMI, positive and negative psychiatric symptoms of patients with schizophrenia.

Notes on the Goodness-of-Fit Tests for the Ordinal Response Model

  • Jeong, Kwang-Mo;Lee, Hyun-Yung
    • 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.

The Diagnostic Assessment of Hand Elevation Test in Carpal Tunnel Syndrome

  • Ma, HyunJin;Kim, Insoo
    • Journal of Korean Neurosurgical Society
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    • v.52 no.5
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    • pp.472-475
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    • 2012
  • Objective : The aim of this study is to establish the value of hand elevation test as a reproducible provocative test for the diagnosis of carpal tunnel syndrome (CTS). Methods : We had a prospective study of 45 hands of 38 patients diagnosed with CTS between April 2005 and February 2009. The diagnosis of CTS was based on the American Academy of Neurology clinical diagnostic criteria. Experimental and control group patients underwent Tinel's test, Phalen's test, carpal compression test and hand elevation test as provocative tests for CTS. Results : We used chi-square analysis to compare Tinel's test and Phalen's test, carpal compression test with hand elevation test. The sensitivity and specificity of the hand elevation test is 86.7% and 88.9% each. Tinel's test had 82.2% sensitivity and 88.9% specificity. Phalen's test had 84.4% sensitivity and 86.7% specificity. Carpal compression test had 84.4% sensitivity 82.2% specificity. Comparisons of sensitivity and specificity between hand elevation test and Tinel's test, Phalen's test, and carpal compression test had no statistically significant differences. To compare the diagnostic accuracies of four tests, the area under the non-parametric receiver operating character curve was applied. Conclusion : The hand elevation test has higher sensitivity and specificity than Tinel's test, Phalen's test, and carpal compression test. Chi-square statistical analysis confirms the hand elevation test is not ineffective campared with Tinel's test, Phalen's test, and carpal compression test.

ON THE GOODNESS OF FIT TEST FOR DISCRETELY OBSERVED SAMPLE FROM DIFFUSION PROCESSES: DIVERGENCE MEASURE APPROACH

  • Lee, Sang-Yeol
    • Journal of the Korean Mathematical Society
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    • v.47 no.6
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    • pp.1137-1146
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    • 2010
  • In this paper, we study the divergence based goodness of fit test for partially observed sample from diffusion processes. In order to derive the limiting distribution of the test, we study the asymptotic behavior of the residual empirical process based on the observed sample. It is shown that the residual empirical process converges weakly to a Brownian bridge and the associated phi-divergence test has a chi-square limiting null distribution.

Bayesian Test of Quasi-Independence in a Sparse Two-Way Contingency Table

  • Kwak, Sang-Gyu;Kim, Dal-Ho
    • Communications for Statistical Applications and Methods
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    • v.19 no.3
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    • pp.495-500
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    • 2012
  • We consider a Bayesian test of independence in a two-way contingency table that has some zero cells. To do this, we take a three-stage hierarchical Bayesian model under each hypothesis. For prior, we use Dirichlet density to model the marginal cell and each cell probabilities. Our method does not require complicated computation such as a Metropolis-Hastings algorithm to draw samples from each posterior density of parameters. We draw samples using a Gibbs sampler with a grid method. For complicated posterior formulas, we apply the Monte-Carlo integration and the sampling important resampling algorithm. We compare the values of the Bayes factor with the results of a chi-square test and the likelihood ratio test.

Extracting the Risk Factor of Ground Excavation Construction and Confidence Analysis using Statistical Test Procedure (지반굴착공사 위험요소 도출 및 통계적 검정 방법을 통한 신뢰성 분석)

  • Kim, Dong-Min;Kim, Woo-Seok;Baek, Yong
    • Journal of Korean Society of Disaster and Security
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    • v.10 no.1
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    • pp.11-17
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    • 2017
  • The case study on ground subsidence was conducted and the cause of ground subsidence was evaluated, main cause were insufficient site exploration, inaccurate strength parameters, defective temporary wall, insufficient reaction for boiling and heaving, excessive excavation and so on. Risk factors during excavation were identified from the cause of ground subsidence and risk factors were site exploration, selecting excavation method, structure analysis, measurement plan, excavation method construction, underground water level change, natural disaster and construction management. The survey of the experts on risk factors identified was conducted to evaluate the importance of risk factors, and confidence analysis was performed to evaluate the significance level between survey result and survey respondent using Chi-square Test.

Comparison of the Power of Bootstrap Two-Sample Test and Wilcoxon Rank Sum Test for Positively Skewed Population

  • Heo, Sunyeong
    • Journal of Integrative Natural Science
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    • v.15 no.1
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    • pp.9-18
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    • 2022
  • This research examines the power of bootstrap two-sample test, and compares it with the powers of two-sample t-test and Wilcoxon rank sum test, through simulation. For simulation work, a positively skewed and heavy tailed distribution was selected as a population distribution, the chi-square distributions with three degrees of freedom, χ23. For two independent samples, the fist sample was selected from χ23. The second sample was selected independently from the same χ23 as the first sample, and calculated d+ax for each sampled value x, a randomly selected value from χ23. The d in d+ax has from 0 to 5 by 0.5 interval, and the a has from 1.0 to 1.5 by 0.1 interval. The powers of three methods were evaluated for the sample sizes 10,20,30,40,50. The null hypothesis was the two population medians being equal for Bootstrap two-sample test and Wilcoxon rank sum test, and the two population means being equal for the two-sample t-test. The powers were obtained using r program language; wilcox.test() in r base package for Wilcoxon rank sum test, t.test() in r base package for the two-sample t-test, boot.two.bca() in r wBoot pacakge for the bootstrap two-sample test. Simulation results show that the power of Wilcoxon rank sum test is the best for all 330 (n,a,d) combinations and the power of two-sample t-test comes next, and the power of bootstrap two-sample comes last. As the results, it can be recommended to use the classic inference methods if there are widely accepted and used methods, in terms of time, costs, sometimes power.