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Marginalized Zero-Inflated Poisson Models with Missing Covariates

Citation

Benecha, Habtamu K.; Preisser, John S.; Divaris, Kimon; Herring, Amy H.; & Das, Kalyan K. (2018). Marginalized Zero-Inflated Poisson Models with Missing Covariates. Biometrical Journal, 60(4), 845-858. PMCID: PMC6453121

Abstract

Unlike zero-inflated Poisson regression, marginalized zero-inflated Poisson (MZIP) models for counts with excess zeros provide estimates with direct interpretations for the overall effects of covariates on the marginal mean. In the presence of missing covariates, MZIP and many other count data models are ordinarily fitted using complete case analysis methods due to lack of appropriate statistical methods and software. This article presents an estimation method for MZIP models with missing covariates. The method, which is applicable to other missing data problems, is illustrated and compared with complete case analysis by using simulations and dental data on the caries preventive effects of a school-based fluoride mouthrinse program.

URL

http://dx.doi.org/10.1002/bimj.201600249

Reference Type

Journal Article

Year Published

2018

Journal Title

Biometrical Journal

Author(s)

Benecha, Habtamu K.
Preisser, John S.
Divaris, Kimon
Herring, Amy H.
Das, Kalyan K.

PMCID

PMC6453121