• 제목/요약/키워드: Modified-Binomial Model

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Comparison of Three Binomial-related Models in the Estimation of Correlations

  • Moon, Myung-Sang
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.585-594
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    • 2003
  • It has been generally recognized that conventional binomial or Poisson model provides poor fits to the actual correlated binary data due to the extra-binomial variation. A number of generalized statistical models have been proposed to account for this additional variation. Among them, beta-binomial, correlated-binomial, and modified-binomial models are binomial-related models which are frequently used in modeling the sum of n correlated binary data. In many situations, it is reasonable to assume that n correlated binary data are exchangeable, which is a special case of correlated binary data. The sum of n exchangeable correlated binary data is modeled relatively well when the above three binomial-related models are applied. But the estimation results of correlation coefficient turn to be quite different. Hence, it is important to identify which model provides better estimates of model parameters(success probability, correlation coefficient). For this purpose, a small-scale simulation study is performed to compare the behavior of above three models.

Tests for homogeneity of proportions in clustered binomial data

  • Jeong, Kwang Mo
    • Communications for Statistical Applications and Methods
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    • 제23권5호
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    • pp.433-444
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    • 2016
  • When we observe binary responses in a cluster (such as rat lab-subjects), they are usually correlated to each other. In clustered binomial counts, the independence assumption is violated and we encounter an extra-variation. In the presence of extra-variation, the ordinary statistical analyses of binomial data are inappropriate to apply. In testing the homogeneity of proportions between several treatment groups, the classical Pearson chi-squared test has a severe flaw in the control of Type I error rates. We focus on modifying the chi-squared statistic by incorporating variance inflation factors. We suggest a method to adjust data in terms of dispersion estimate based on a quasi-likelihood model. We explain the testing procedure via an illustrative example as well as compare the performance of a modified chi-squared test with competitive statistics through a Monte Carlo study.

불완전 디버깅 환경에서의 이항 반응 계수 초기하분포 소프트웨어 신뢰성 성장 모델 (The Binomial Sensitivity Factor Hyper-Geometric Distribution Software Reliability Growth Model for Imperfect Debugging Environment)

  • 김성희;박중양;박재흥
    • 한국정보처리학회논문지
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    • 제7권4호
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    • pp.1103-1111
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    • 2000
  • The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

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Evaluation of Related Risk Factors in Number of Musculoskeletal Disorders Among Carpet Weavers in Iran

  • Karimi, Nasim;Moghimbeigi, Abbas;Motamedzade, Majid;Roshanaei, Ghodratollah
    • Safety and Health at Work
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    • 제7권4호
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    • pp.322-325
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    • 2016
  • Background: Musculoskeletal disorders (MSDs) are a common problem among carpet weavers. This study was undertaken to introduce affecting personal and occupational factors in developing the number of MSDs among carpet weavers. Methods: A cross-sectional study was performed among 862 weavers in seven towns with regard to workhouse location in urban or rural regions. Data were collected by using questionnaires that contain personal, workplace, and information tools and the modified Nordic MSDs questionnaire. Statistical analysis was performed by applying Poisson and negative binomial mixed models using a full Bayesian hierarchical approach. The deviance information criterion was used for comparison between models and model selection. Results: The majority of weavers (72%) were female and carpet weaving was the main job of 85.2% of workers. The negative binomial mixed model with lowest deviance information criterion was selected as the best model. The criteria showed the convergence of chains. Based on 95% Bayesian credible interval, the main job and weaving type variables statistically affected the number of MSDs, but variables age, sex, weaving comb, work experience, and carpet weaving looms were not significant. Conclusion: According to the results of this study, it can be concluded that occupational factors are associated with the number of MSDs developing among carpet weavers. Thus, using standard tools and decreasing hours of work per day can reduce frequency of MSDs among carpet weavers.

Novel nomogram-based integrated gonadotropin therapy individualization in in vitro fertilization/intracytoplasmic sperm injection: A modeling approach

  • Ebid, Abdel Hameed IM;Motaleb, Sara M Abdel;Mostafa, Mahmoud I;Soliman, Mahmoud MA
    • Clinical and Experimental Reproductive Medicine
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    • 제48권2호
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    • pp.163-173
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    • 2021
  • Objective: This study aimed to characterize a validated model for predicting oocyte retrieval in controlled ovarian stimulation (COS) and to construct model-based nomograms for assistance in clinical decision-making regarding the gonadotropin protocol and dose. Methods: This observational, retrospective, cohort study included 636 women with primary unexplained infertility and a normal menstrual cycle who were attempting assisted reproductive therapy for the first time. The enrolled women were split into an index group (n=497) for model building and a validation group (n=139). The primary outcome was absolute oocyte count. The dose-response relationship was tested using modified Poisson, negative binomial, hybrid Poisson-Emax, and linear models. The validation group was similarly analyzed, and its results were compared to that of the index group. Results: The Poisson model with the log-link function demonstrated superior predictive performance and precision (Akaike information criterion, 2,704; λ=8.27; relative standard error (λ)=2.02%). The covariate analysis included women's age (p<0.001), antral follicle count (p<0.001), basal follicle-stimulating hormone level (p<0.001), gonadotropin dose (p=0.042), and protocol type (p=0.002 and p<0.001 for short and antagonist protocols, respectively). The estimates from 500 bootstrap samples were close to those of the original model. The validation group showed model assessment metrics comparable to the index model. Based on the fitted model, a static nomogram was built to improve visualization. In addition, a dynamic electronic tool was created for convenience of use. Conclusion: Based on our validated model, nomograms were constructed to help clinicians individualize the stimulation protocol and gonadotropin doses in COS cycles.

수정된 제1종 부분 응답 전송 시스템 모델을 이용한 여현 펄스 푸리에 변환의 새로운 순환 공식 (A New Recursive Formula to Derive the Fourier Transforms of Cosine-Pulses Using Modified Class-I PRS Model)

  • 오용선;조형래;강민구;김한종;강창언
    • 한국통신학회논문지
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    • 제17권12호
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    • pp.1343-1352
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    • 1992
  • 본 논문에서는 일정한 구간 내에 한정되고 최대치가 균일하도록 설정된 임의 차수 여현펄스의 푸리에 변환을 유도하기 위한 새롭고 용이한 방법을 제안하였다. 제안된 방법은 수치적 해법에 원활하게 적용될 수 있도록 함수의 각 차수에 따라 순환적으로 유도되는 공식에 초점을 두고 있다. 반면에, 유도된 관계식은 용이하게 계산될 수 있는 두함수의 합에 의하여 나타나므로 해석적 해법의 관점에서도 기존의 방법보다 간결한 과정을 제공한다. 특히, 저자 등에 의하여 발견된 계수 분리법에 의하여 공식은 완전 순환적 알고리듬으로 표현되며, 그 결과로 나타나는 자동방정식은 초기 'Sinc'함수가 차수에 따라 지연되어 상수가 곱해진 형태의 합으로 주어진다. 이 때 곱해지는 각 상수는 이항계수로부터 용이하게 결정되며, 'Sinc'함수의 지연요소도 이항식 $(a+b)^n$의 전개식에서 해당되는 항의 지수차에 의하여 쉽게 얻어진다.

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