The Paradoxical Nature of The Proportional Hazards Model of Random Censorship
Sándor CsörgőDepartment of Statistics , University of Michigan , 48109-1027, Ann Arbor, MI, USA , 1440 Mason HallJulian J. FarawayDepartment of Statistics , University of Michigan , 48109-1027, Ann Arbor, MI, USA , 1440 Mason Hall
1998en
ABI
Annotatsiya
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 xbelow the 0.56-quantile of F.
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