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Extension of GLM for Bivariate Data

In: Generalized Linear Models and Extensions

Author

Listed:
  • M. Ataharul Islam

    (University of Dhaka, ISRT)

  • Soma Chowdhury Biswas

    (University of Chittagong, Department of Statistics)

Abstract

In this chapter, the models are developed for correlated outcomes where the association parameters are of interest. The models are based on marginal-conditional approachMarginal-conditional approach and generalized linear models are developed for discrete and continuous random variables. Islam and Chowdhury, PLoS ONE 12, (2017a), Islam and Chowdhury, Analysis of repeated measures data, Springer (2017b) provided introduction to bivariate models for different types of data. The conditional models are presented along with bivariate models using multiplication where joint probability distribution is shown by multiplying the conditional probability with marginal probability. The exponential forms, generalized linear model representations, over-dispersion problems and remedial measures, measures of goodness of fit, devianceDeviance, and testing of hypotheses are discussed with emphasis to make the users understand the concepts without difficulty.

Suggested Citation

  • M. Ataharul Islam & Soma Chowdhury Biswas, 2025. "Extension of GLM for Bivariate Data," Springer Books, in: Generalized Linear Models and Extensions, chapter 0, pages 139-161, Springer.
    • Handle: RePEc:spr:sprchp:978-981-96-4726-2_8
    DOI: 10.1007/978-981-96-4726-2_8
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