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A GEE-type approach to untangle structural and random zeros in predictors.
- Source :
- Statistical Methods in Medical Research; Dec2019, Vol. 28 Issue 12, p3683-3696, 14p
- Publication Year :
- 2019
-
Abstract
- Count outcomes with excessive zeros are common in behavioral and social studies, and zero-inflated count models such as zero-inflated Poisson (ZIP) and zero-inflated Negative Binomial (ZINB) can be applied when such zero-inflated count data are used as response variable. However, when the zero-inflated count data are used as predictors, ignoring the difference of structural and random zeros can result in biased estimates. In this paper, a generalized estimating equation (GEE)-type mixture model is proposed to jointly model the response of interest and the zero-inflated count predictors. Simulation studies show that the proposed method performs well for practical settings and is more robust for model misspecification than the likelihood-based approach. A case study is also provided for illustration. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09622802
- Volume :
- 28
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Statistical Methods in Medical Research
- Publication Type :
- Academic Journal
- Accession number :
- 138612385
- Full Text :
- https://doi.org/10.1177/0962280218812228