Advances and Applications in Statistics

The Advances and Applications in Statistics is an internationally recognized journal indexed in the Emerging Sources Citation Index (ESCI). It provides a platform for original research papers and survey articles in all areas of statistics, both computational and experimental in nature.

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COMPARING POISSON RATES WHEN DATA ARE SUBJECT TO UNDERREPORTING

Authors

  • James D. Stamey

Keywords:

bootstrap, misclassification, count data

DOI:

https://doi.org/10.17654/0972361724071

Abstract

Count data are often modeled with the Poisson distribution. Comparison of two Poisson rates can be done using the conditional test based on the binomial assumption. When the counts are underreported, the power of the conditional test can be impacted. We propose a large sample normal test and a small sample parametric bootstrap test based on estimators corrected for underreporting via a double sample. An example is given.

Received: June 18, 2024
Revised: July 3, 2024
Accepted: July 19, 2024

References

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C. Anderson, T. Bratcher and K. Kutron, Bayesian estimation of population density and visibility, Texas Journal of Science 46 (1994), 7-12.

D. Sengupta, S. Roy and T Banerjee, Testing of Poisson mean with under-reported counts, Braz. J. Probab. Stat. 35 (2021), 523-543.

D. Sengupta and S. Roy, Modelling zero inflated and under-reported count data, J. Stat. Comput. Simul. 93 (2023), 2390-2409.

R. Fantin, C. Barboza-Solis, A. Hildesheim and R. Herrero, Excess mortality from COVID 19 in Costa Rica: a registry-based study using Poisson regression, The Lancet Regional Health - Americas 20 (2023), 100451.

J. Chen, J. Song and J. Stamey, A Bayesian hierarchical spatial model to correct for misreporting in count data: application to state-level COVID-19 data in the United States, International Journal of Environmental Research and Public Health 19 (2022), 3327.

E. Kupek, How many more? Under-reporting of the COVID-19 deaths in Brazil in 2020, Tropical Medicine and International Health 26 (2021), 1019-1028.

J. S. Stamey, D. M. Young and M. Cecchini, A double-sampling approach for maximum likelihood estimation for a Poisson rate parameter with visibility bias, Statistica 63 (2003), 3-11.

Published

14-09-2024

Issue

Section

Articles

How to Cite

COMPARING POISSON RATES WHEN DATA ARE SUBJECT TO UNDERREPORTING. (2024). Advances and Applications in Statistics , 91(11), 1375-1386. https://doi.org/10.17654/0972361724071

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