Please use this identifier to cite or link to this item:
PIRA download icon_1.1View/Download Full Text
Title: Modified Poisson regression analysis of grouped and right-censored counts
Authors: Fu, Q
Zhou, TY
Guo, X 
Issue Date: Oct-2021
Source: Journal of the Royal Statistical Society series A, Oct. 2021, v. 184, no. 4, p. 1347-1367
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.
Keywords: Fisher information
Grouped and right-censored counts
Hybrid line search
Modified Poisson estimators
Regression analysis
Zero inflation
Publisher: Oxford University Press
Journal: Journal of the Royal Statistical Society series A 
ISSN: 0964-1998
EISSN: 1467-985X
DOI: 10.1111/rssa.12678
Rights: © 2021 Royal Statistical Society
This is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of the Royal Statistical Society Series A: Statistics in Society following peer review. The version of record Qiang Fu, Tian-Yi Zhou, Xin Guo, Modified Poisson Regression Analysis of Grouped and Right-Censored Counts, Journal of the Royal Statistical Society Series A: Statistics in Society, Volume 184, Issue 4, October 2021, Pages 1347–1367 is available online at:
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Fu_Modified_Poisson_Regression.pdfPre-Published version777.44 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

Last Week
Last month
Citations as of Jun 4, 2023


Citations as of Jun 4, 2023


Citations as of Jun 2, 2023


Citations as of Jun 1, 2023

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.