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has been cited by the following article:

• TITLE: Quasi-Binomial Regression Model for the Analysis of Data with Extra-Binomial Variation

  AUTHORS: Mohamed M. Shoukri, Maha M. Aleid

  KEYWORDS: Quasi-Binomial Distribution, Extra Binomial Variations, Score Test, Quasi-Binomial Regression Model, COVID-19 Case Fatality Data

  JOURNAL NAME: Open Journal of Statistics, Vol.12 No.1, January 29, 2022

  ABSTRACT: Objectives: Developing inference procedures on the quasi-binomial distribution and the regression model. Methods: Score testing and the method of maximum likelihood for regression parameters estimation. Data: Several examples are included, based on published data. Results: A quasi-binomial model is used to model binary response data which exhibit extra-binomial variation. A partial score test on the binomial hypothesis versus the quasi-binomial alternative is developed and illustrated on three data sets. The extended logit transformation on the binomial parameter is introduced and the large sample dispersion matrix of the estimated parameters is derived. The Nonlinear Mixed Procedure (NLMIXED) in SAS is shown to be very appropriate for the estimation of nonlinear regression.