We show that the proportional hazards model of random censorship is too good to be frequently true as measured by mean squared errors: for estimating the underlying distribution function F(x) it is better to have a censored sample for a suitable expected censoring proportion than an uncensored full sample of the same size for any x below the 0.56-quantile of F.
- Censored and uncensored samples
- Proportional hazards
- Random censorship
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty