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Multi-parameter regression survival models

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conference contribution
posted on 2022-11-12, 11:25 authored by Kevin BurkeKevin Burke, Gilbert MackenzieGilbert Mackenzie
The proportional hazards (PH) assumption in survival analysis may not always be appropriate. If data do not obey the assumption then we will reach incorrect conclusions by making it. For example we may find a covariate to be statistically insignificant when in fact it is important, but on a non-PH scale. Even if a PH model does pick up the statistical significance of such a 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 parametric PH modelling which we call multi-parameter regression, MPR, modelling.

Funding

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

National Research Foundation

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History

Publication

28th International Workshop on Statistical Modelling,Vito M.R. Muggeo, Vincenza Capursi, Giovanni Boscaino, Gianfranco Lovison (Eds.);

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

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