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Modified Poisson regression analysis of grouped and right‐censored counts

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  • Qiang Fu
  • Tian‐Yi Zhou
  • Xin Guo

Abstract

Grouped and right‐censored (GRC) counts are widely used in criminology, demography, epidemiology, marketing, sociology, psychology and other related disciplines to study behavioural and event frequencies, especially when sensitive research topics or individuals with possibly lower cognitive capacities are at stake. Yet, the co‐existence of grouping and right‐censoring poses major difficulties in regression analysis. To implement generalised linear regression of GRC counts, we derive modified Poisson estimators and their asymptotic properties, develop a hybrid line search algorithm for parameter inference, demonstrate the finite‐sample performance of these estimators via simulation, and evaluate its empirical applicability based on survey data of drug use in America. This method has a clear methodological advantage over the ordered logistic model for analysing GRC counts.

Suggested Citation

  • Qiang Fu & Tian‐Yi Zhou & Xin Guo, 2021. "Modified Poisson regression analysis of grouped and right‐censored counts," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1347-1367, October.
    • Handle: RePEc:bla:jorssa:v:184:y:2021:i:4:p:1347-1367
    DOI: 10.1111/rssa.12678
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    References listed on IDEAS

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    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, September.
    2. Patrick Royston, 2007. "Multiple imputation of missing values: further update of ice, with an emphasis on interval censoring," Stata Journal, StataCorp LP, vol. 7(4), pages 445-464, December.
    3. Qiang Fu & Xin Guo & Kenneth C. Land, 2018. "A Poisson-multinomial mixture approach to grouped and right-censored counts," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(2), pages 427-447, January.
    4. David G. Luenberger & Yinyu Ye, 2016. "Linear and Nonlinear Programming," International Series in Operations Research and Management Science, Springer, edition 4, number 978-3-319-18842-3, April.
    5. Qiang Fu & Xin Guo & Kenneth C. Land, 2020. "Optimizing Count Responses in Surveys: A Machine-learning Approach," Sociological Methods & Research, , vol. 49(3), pages 637-671, August.
    6. Rafal Raciborski, 2011. "Right-censored Poisson regression model," Stata Journal, StataCorp LP, vol. 11(1), pages 95-105, March.
    7. Daniel B. Hall, 2000. "Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study," Biometrics, The International Biometric Society, vol. 56(4), pages 1030-1039, December.
    8. Tammy H. Cummings & James W. Hardin & Alexander C. McLain & James R. Hussey & Kevin J. Bennett & Gina M. Wingood, 2015. "Modeling heaped count data," Stata Journal, StataCorp LP, vol. 15(2), pages 457-479, June.
    9. Derek S. Young & Andrew M. Raim & Nancy R. Johnson, 2017. "Zero-inflated modelling for characterizing coverage errors of extracts from the US Census Bureau's Master Address File," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 73-97, January.
    10. S. Zinn & A. Würbach, 2016. "A statistical approach to address the problem of heaping in self-reported income data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(4), pages 682-703, March.
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