We show that the proportional hazards model of random censorship is to
o good to be frequently true as measured by mean squared errors: for e
stimating the underlying distribution function F(x) it is better to ha
ve 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-q
uantile of F.