| Autor: |
Miguel Angel Luque-Fernandez, Aurélien Belot, Manuela Quaresma, Camille Maringe, Michel P. Coleman, Bernard Rachet |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
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| Zdroj: |
BMC Medical Research Methodology, Vol 16, Iss 1, Pp 1-8 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2288 |
| DOI: |
10.1186/s12874-016-0234-z |
| Popis: |
Abstract Background In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. Methods We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. Results All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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