Abstract
A trivariate Bernoulli regression model is proposed in this paper. There is extensive need for analysing repeated binary outcomes where correlated binary outcomes are obtained from repeated measure...
Highlights
The use of Bernoulli regression model is well established
He was a visiting faculty at the University of Hawaii and University of Pennsylvania. He is recipient of the Pauline Stitt Award, the WNAR Biometric Society Award for content and writing, University Grants Commission Award for book and research, Ibrahim Gold Medal for research, etc. He published more than 100 research papers in international journals on various topics, extensively on longitudinal and repeated measures data, including multistate and multistage hazards models, statistical models for repeated measures data, Markov models with covariate dependence, generalized linear models, conditional and joint models for correlated outcomes, etc
The modelling of correlated outcome variables have been of interest in many fields due to recent emergence of need for analysing repeated measures data in the presence of correlation among outcome variables in addition to models for identifying explanatory variables associated with outcome variables
Summary
The use of Bernoulli regression model is well established. The logistic regression model has been one of the most extensively used techniques in various applications which is based on univariate Bernoulli distribution. Since the development of generalized linear models, it has been presented more explicitly using the logit link function from exponential family of distributions for binary data. There have been attempts to develop regression models for bivariate and multivariate Bernoulli regression models.
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