| Summary: | The Cox regression model is widely used for
survival data analysis. The Cox model requires a proportional
hazard. If the proportional hazard assumption is doubfult, then
the additive hazard model can be used, where the covariates
act in an additively to the baseline hazard function. If the
observed survival time is more than once for one individual
during the observation, it is called a recurrent event. The
additive hazard model measures risk difference to the effect
of a covariate in absolutely, while the proportional hazards
model measure hazard ratio in relatively. The risk coefficients
estimation in the additive hazard model mimics the multiplicative
hazard model, using partial likelihood methods. The
derivation of these estimators, outlined in the technical notes,
is based on the counting process approach. The counting
process approach was first developed by Aalen on 1975 which
combines elements of stochastic integration, martingale theory
and counting process theory. The method is applied to study
about the effect of supplementation on infant growth and
development. Based on the processing results, the factors that
affect the growth and development of the infant are gender,
treatment and mother’s education.
|
|---|