A Zero Inflated Regression Model for Grouped Data
We introduce the (panel) zero-inflated interval regression (ZIIR) model, which is ideally suited when data are in the form of groups, which is commonly the case in survey data, and there is an ‘excess’ of zero observations. We apply our new modelling framework to the analysis of visits to general practitioners (GPs) using individual-level panel data from the British Household Panel Survey (BHPS). The ZIIR model simultaneously estimates the probability of visiting the GP and the frequency of visits (defined by given numerical intervals in the data). The results show that different socio-economic factors influence the probability of visiting the GP and the frequency of visits, thereby providing potentially valuable information to policy-makers concerned with health care allocation.
|Date of creation:||Jan 2014|
|Contact details of provider:|| Web page: http://business.curtin.edu.au/bcec|
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MIT Press Books,
The MIT Press,
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- Wang, Peiming, 2003. "A bivariate zero-inflated negative binomial regression model for count data with excess zeros," Economics Letters, Elsevier, vol. 78(3), pages 373-378, March.
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