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