1. A GEE-type approach to untangle structural and random zeros in predictors.
- Author
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Ye, Peng, Tang, Wan, He, Jiang, and He, Hua
- Subjects
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GENERALIZED estimating equations , *SOCIAL sciences education , *ROBUST control , *STATISTICS , *RESEARCH , *BEHAVIORAL research , *RESEARCH methodology , *EVALUATION research , *MEDICAL cooperation , *COMPARATIVE studies , *FORECASTING , *RESEARCH funding , *STATISTICAL models , *DATA analysis , *ALGORITHMS , *PROBABILITY theory - 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]
- Published
- 2019
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