Abstract
This paper develops stochastic search variable selection (SSVS) for zero-inflated
count models which are commonly used in health economics. This allows for
either model averaging or model selection in situations with many potential
regressors. The proposed techniques are applied to a data set from Germany
considering the demand for health care. A package for the free statistical software environment R is provided.
count models which are commonly used in health economics. This allows for
either model averaging or model selection in situations with many potential
regressors. The proposed techniques are applied to a data set from Germany
considering the demand for health care. A package for the free statistical software environment R is provided.
Original language | English |
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Place of Publication | Glasgow |
Publisher | University of Strathclyde |
Pages | 1-20 |
Number of pages | 21 |
Volume | 04 |
Publication status | Published - Oct 2009 |
Keywords
- bayesian
- model selection
- model averaging
- count data
- zero-inflation
- demand for health care