Random effect exponentiated-exponential geometric model for clustered/longitudinal zero-inflated count data

Leili Tapak, Omid Hamidi, Payam Amini and Geert Verbeke

Journal of Applied Statistics, 2020, vol. 47, issue 12, 2272-2288

Abstract: For count responses, there are situations in biomedical and sociological applications in which extra zeroes occur. Modeling correlated (e.g. repeated measures and clustered) zero-inflated count data includes special challenges because the correlation between measurements for a subject or a cluster needs to be taken into account. Moreover, zero-inflated count data are often faced with over/under dispersion problem. In this paper, we propose a random effect model for repeated measurements or clustered data with over/under dispersed response called random effect zero-inflated exponentiated-exponential geometric regression model. The proposed method was illustrated through real examples. The performance of the model and asymptotical properties of the estimations were investigated using simulation studies.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:47:y:2020:i:12:p:2272-2288

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DOI: 10.1080/02664763.2019.1706726

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