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. 2011 Aug 15;30(18):2326-40.
doi: 10.1002/sim.4268. Epub 2011 May 12.

New variable selection methods for zero-inflated count data with applications to the substance abuse field

Anne Buu  1 , Norman J Johnson, Runze Li, Xianming Tan
Affiliations

New variable selection methods for zero-inflated count data with applications to the substance abuse field

Anne Buu et al. Stat Med. .

Abstract

Zero-inflated count data are very common in health surveys. This study develops new variable selection methods for the zero-inflated Poisson regression model. Our simulations demonstrate the negative consequences which arise from the ignorance of zero-inflation. Among the competing methods, the one-step SCAD method is recommended because it has the highest specificity, sensitivity, exact fit, and lowest estimation error. The design of the simulations is based on the special features of two large national databases commonly used in the alcoholism and substance abuse field so that our findings can be easily generalized to the real settings. Applications of the methodology are demonstrated by empirical analyses on the data from a well-known alcohol study.

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Figures

Figure 1
Figure 1. Distributions of DSM-IV alcohol use disorder symptom counts
See this image and copyright information in PMC

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