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

Juxin Liu, Yanyuan Ma, Jill Johnstone

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article number106887
JournalComputational Statistics and Data Analysis
Volume144
DOIs
StatePublished - Apr 2020

Fingerprint

Mixed Effects Model
Goodness of Fit Test
Siméon Denis Poisson
Sampling
Zero
Ecology
Vary
Mixed Effects
Cumulative Sum
Field Study
Sampling Design
Poisson Model
Convergence Properties
Arrangement
Count
Disturbance
Simulation Study
Modeling
Model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

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A goodness-of-fit test for zero-inflated Poisson mixed effects models in tree abundance studies. / Liu, Juxin; Ma, Yanyuan; Johnstone, Jill.

In: Computational Statistics and Data Analysis, Vol. 144, 106887, 04.2020.

Research output: Contribution to journalArticle

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