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From | "Scott Holupka" <Scott.Holupka@jhu.edu> |
To | <statalist@hsphsun2.harvard.edu> |
Subject | st: Zero Inflated Poisson Regression |
Date | Mon, 6 Aug 2012 13:48:32 -0400 |
This is mainly a question about running a zero-inflated poisson regression using zip (Stata 10.1), but it's also a more general question of whether Statalisters think I'm using the procedures in an appropriate way. My analysis is examining several expenditure categories. Typical of expenditure data, the outcome variables are all skewed. Also typical is that several outcomes have a large percentage (20% to 40%) of cases reporting zero. I am therefore considering using zero-inflated poisson models - zip - to examine these outcomes. Prior research also suggests that the relationship between our primary independent variable - call it H - and expenditures will not be linear. In particular, we expect spending may be lower at both high and low values of H. I have previously used polynominal models to examine this relationship, but I'm not sure if polynomials can be used with negative poissson models. I am therefore also considering using a piecewise regression approach with ZIP. Finally, I'm concerned about omitted variable bias since I don't have a randomized sample. Again, in previous work I've used propensity score methods to account for differences in observed characteristics. I know how to implement each of these methods in Stata, but I'm wondering if it's appropriate to use all three methods at once. My current plan is to run propensity analyses to identify similar groups based on observed characteristics, then use those groups as covariates in a zero-inflated poisson model that also include polynomial terms of H (e.g. H and H-squared), or computing piecewise dummy variables of H. Any thoughts on whether this approach seems appropriate, particularly whether ZIP can handle both the propensity covariates and polynomial terms, would be appreciated. Thanks, Scott * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/