A goodness-of-fit test for zero-inflated Poisson mixed effects models in tree abundance studies

Juxin Liu, Yanyuan Ma and Jill Johnstone

Computational Statistics & Data Analysis, 2020, vol. 144, issue C

Abstract: Field studies in ecology often make use of data collected in a hierarchical fashion, and may combine studies that vary in sampling design. For example, studies of tree recruitment after disturbance may use counts of individual seedlings from plots that vary in spatial arrangement and sampling density. To account for the multi-level design and the fact that more than a few plots usually yield no individuals, a mixed effects zero inflated Poisson model is often adopted. Although it is a convenient modeling strategy, various aspects of the model could be misspecified. A comprehensive test procedure, based on the cumulative sum of the residuals, is proposed. The test is proven to be consistent, and its convergence properties are established as well. The application of the proposed test is illustrated by a real data example and simulation studies.

Keywords: Goodness-of-fit test; Poisson zero-inflated model; Random effects; Cumulative sum of the residuals (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:144:y:2020:i:c:s0167947319302427

DOI: 10.1016/j.csda.2019.106887

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