University of Limerick
Browse
Mackenzie_2012_multi-parameter.pdf (200.88 kB)

Multi-parameter regression survival models

Download (200.88 kB)
conference contribution
posted on 2022-11-11, 19:50 authored by Kevin BurkeKevin Burke, Gilbert MackenzieGilbert Mackenzie
It is well known that the proportional hazards (PH) assumption is a simplifying assumption in survival analysis that may not always be appropriate. However, PH models are routinely fitted and inference is made on the data based on such models. A major flaw here is that if the data are non-PH then we will reach incorrect conclusions by making this assumption. For example we may find a covariate to be statistically insigni cant when in fact it is important, but the model fails to pick this up. Even if a PH model does pick up the statistical significance of a non-PH covariate, the nature of the effect of the covariate on survival, as determined by this simplistic model, will clearly be incorrect. We introduce a regression-based extension of PH modelling to try an account for situations such as those described above and offer new, previously unavailable insights, into the data.

Funding

A new method for transforming data to normality with application to density estimation

National Research Foundation

Find out more...

History

Publication

Proceedings of the 27th International Workshop on Statistical Modelling;

Publisher

IWSM

Note

peer-reviewed

Other Funding information

SFI, IRCSET

Language

English

Also affiliated with

  • BIO-SI - Bio-Statistics & Informatics Project

Department or School

  • Mathematics & Statistics

Usage metrics

    University of Limerick

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC