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.

Keywords and Phrases

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

A.M.S. subject classification

62J12

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