Compare Predicted Counts Between Groups of Zero-Truncated Poisson Regression Model Based on Recycled Predictions Method

• Activity Number: 314
• Type: Contributed
• Date/Time: Tuesday, August 2, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Yan Wang*+ and Michael Ong and Honghu Liu
• Companies: University of California at Los Angeles and University of California at Los Angeles and University of California at Los Angeles
• Keywords: Zero Truncated Poisson (ZTP) regression model ; recycled predictions method ; variance estimation

Abstract

Zero Truncated Poisson (ZTP) regression model is used to model positive count data, where zero is a potential value but is almost impossible to be observed due to the nature of study and its design. ZTP is more accurate than traditional Poisson regression model for this kind of data. In practice, researchers often need to test the difference of the predicted counts between groups with ZTP regression model. The test result can be misleading if the design is very unbalanced. However, the combination of ZTP regression model and recycled predictions method is one possible way to create an identical structure of the covariates when comparing the predicted counts between groups. This paper uses ZTP regression model based on recycled predictions method to model the positive count data and estimates the variance of the difference of the predicted counts by delta method. Finally, the model and es