GENERALISED BERNOULLI MODEL FOR CORRELATED BINARY RESPONSES: APPLICATION TO THE NATIONAL INCOME DYNAMICS STUDY (NIDS) DATASETS

Mawutor Fleku, Ezekiel N.N. Nortey, Anani Lotsi, Kwabena Doku-Amponsah

Research output: Contribution to journalArticlepeer-review

Abstract

The bivariate Bernoulli model was used to estimate covariate parameters for conditional as well as marginal models for the NIDs datasets.The covariate parameters were estimated by first expressing the proposed model in the exponential family form, finding the log-likelihood function and then the corresponding estimating equations. The Nelder Mead method of iteration was used to estimate the covariate parameters. The research revealed that the bivariate Bernoulli model fitted bivariate binary response data significantly better than the conditional logistic and the Generalized Estimating Equation (GEE) logistic marginal model. The result was same for both artificial and real-life data.

Original languageEnglish
Pages (from-to)71-88
Number of pages18
JournalSouth East Asian Journal of Mathematics and Mathematical Sciences
Volume15
Issue number1
Publication statusPublished - Apr 2019

Keywords

  • Correlated binary responses
  • joint modeling
  • likelihood ratio test
  • longitudinal study
  • pre and post testing

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