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Be wary of using Poisson regression to estimate risk and relative risk
Citation
Zhu, C and Blizzard, L and Stankovich, J and Wills, K and Hosmer, DW, Be wary of using Poisson regression to estimate risk and relative risk, Biostatistics and Biometrics Open Access Journal, 4, (5) Article 555649. ISSN 2573-2633 (2018) [Refereed Article]
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Copyright Statement
Copyright © All rights are reserved by Blizzard L. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/
Official URL: https://juniperpublishers.com/bboaj/BBOAJ.MS.ID.55...
DOI: doi:10.19080/BBOAJ.2018.04.555649
Abstract
Fitting a log binomial model to binary outcome data makes it possible to estimate risk and relative risk for follow-up data, and prevalence
and prevalence ratios for cross-sectional data. However, the fitting algorithm may fail to converge when the maximum likelihood solution is on
the boundary of the allowable parameter space. Some authorities recommend switching to Poisson regression with robust standard errors to
approximate the coefficients of the log binomial model in those circumstances. This solves the problem of non-convergence, but results in errors
in the coefficient estimates that may be substantial particularly when the maximum fitted value is large. The paradox is that the circumstances
in which the modified Poisson approach is needed to overcome estimation problems are the same circumstances when the error in using it is
greatest. We recommend that practitioners should be wary of using modified Poisson regression to approximate risk and relative risk.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | relative risk, log binomial model, Poisson regression, boundary point |
| Research Division: | Mathematical Sciences |
| Research Group: | Statistics |
| Research Field: | Biostatistics |
| Objective Division: | Health |
| Objective Group: | Public health (excl. specific population health) |
| Objective Field: | Public health (excl. specific population health) not elsewhere classified |
| UTAS Author: | Zhu, C (Mr Chao Zhu) |
| UTAS Author: | Blizzard, L (Professor Leigh Blizzard) |
| UTAS Author: | Stankovich, J (Dr Jim Stankovich) |
| UTAS Author: | Wills, K (Dr Karen Wills) |
| ID Code: | 135470 |
| Year Published: | 2018 |
| Deposited By: | Menzies Institute for Medical Research |
| Deposited On: | 2019-10-23 |
| Last Modified: | 2020-12-18 |
| Downloads: | 19 View Download Statistics |
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