Modified Poisson regression analysis of grouped and right-censored counts

Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90344

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:	Wiley-Blackwell Publishing
Journal:	Journal of the Royal Statistical Society series A
ISSN:	0964-1998
EISSN:	1467-985X
DOI:	10.1111/rssa.12678
Appears in Collections:	Journal/Magazine Article

Status	embargoed access
Embargo End Date	2022-10-31

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