TY - JOUR
T1 - A goodness-of-fit test for zero-inflated Poisson mixed effects models in tree abundance studies
AU - Liu, Juxin
AU - Ma, Yanyuan
AU - Johnstone, Jill
N1 - Funding Information:
The first author's work is supported by an NSERC, Canada grant. The second author's work is supported by National Science Foundation (NSF), USA and NIH, USA grants. The last author's work is supported by grants from NSERC, Canada, the US SERDP program (RC-2109), and US LTER (NSF DEB-0620579). The authors are thankful to the anonymous reviewers for their valuable comments that have greatly improved the manuscript.
Funding Information:
The first author’s work is supported by an NSERC, Canada grant. The second author’s work is supported by National Science Foundation (NSF), USA and NIH, USA grants. The last author’s work is supported by grants from NSERC, Canada , the US SERDP program ( RC-2109 ), and US LTER (NSF DEB-0620579). The authors are thankful to the anonymous reviewers for their valuable comments that have greatly improved the manuscript. Appendix
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/4
Y1 - 2020/4
N2 - 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.
AB - 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.
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U2 - 10.1016/j.csda.2019.106887
DO - 10.1016/j.csda.2019.106887
M3 - Article
C2 - 32153310
AN - SCOPUS:85075780856
SN - 0167-9473
VL - 144
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
M1 - 106887
ER -