A generalized right truncated bivariate Poisson regression model with applications to health data

PLoS One. 2017 Jun 6;12(6):e0178153. doi: 10.1371/journal.pone.0178153. eCollection 2017.

Abstract

A generalized right truncated bivariate Poisson regression model is proposed in this paper. Estimation and tests for goodness of fit and over or under dispersion are illustrated for both untruncated and right truncated bivariate Poisson regression models using marginal-conditional approach. Estimation and test procedures are illustrated for bivariate Poisson regression models with applications to Health and Retirement Study data on number of health conditions and the number of health care services utilized. The proposed test statistics are easy to compute and it is evident from the results that the models fit the data very well. A comparison between the right truncated and untruncated bivariate Poisson regression models using the test for nonnested models clearly shows that the truncated model performs significantly better than the untruncated model.

MeSH terms

  • Accidents, Traffic / statistics & numerical data
  • Data Interpretation, Statistical*
  • Female
  • Health Personnel / statistics & numerical data*
  • Health Services Research / statistics & numerical data*
  • Humans
  • Male
  • Models, Statistical
  • Poisson Distribution
  • Racial Groups

Grants and funding

The study is supported by the HEQEP sub-project 3293, University Grants Commission of Bangladesh and the World Bank.