Abstract
We consider a semi-parametric model for recurrent events. The model consists of an unknown hazard rate function, the infinite-dimensional parameter of the model, and a parametrically specified effective age function. We will present a condition on the family of effective age functions under which the profile likelihood function evaluated at the parameter vector theta, say, exceeds the profile likelihood function evaluated at the parameter vector (theta) over bar, say, with probability p. From this we derive a condition under which profile likelihood inference for the finite-dimensional parameter of the model leads to inconsistent estimates. Examples will be presented. In particular, we will provide an example where the profile likelihood function is monotone with probability one regardless of the true data generating process. We also discuss the relation of our results to other semi-parametric models like the accelerated failure time model and Cox's proportional hazards model.
Original language | English |
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Pages (from-to) | 3650-3684 |
Journal | Bernoulli |
Volume | 23 |
Issue number | 4B |
DOIs | |
Publication status | Published - Nov 2017 |
Keywords
- accelerated failure time model
- Cox's proportional hazards model
- effective age process
- profile likelihood inference
- recurrent event data
- semi-parametric statistical model
- virtual age process