Modified Poisson Regression Analysis of Grouped and Right-Censored Counts
| Autor: | Qiang Fu, Xin Guo, Tian Yi Zhou |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Economics and Econometrics Inference Estimator Regression analysis Poisson distribution Logistic regression symbols.namesake Statistics Linear regression symbols Poisson regression Statistics Probability and Uncertainty Psychology Fisher information Social Sciences (miscellaneous) |
| Zdroj: | Journal of the Royal Statistical Society Series A: Statistics in Society. 184:1347-1367 |
| ISSN: | 1467-985X 0964-1998 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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