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Department of Statistics, University of Adelaide, South Australia.
We present analyses for survival data obtained from a central cancer registry with passive follow-up. This method of data collection has the potential to produce unknown random losses which would affect estimates of survival. We show that non-parametrically estimated conditional distributions remove any effect of these unknown losses and that a compound mixture model estimates their magnitude. Lung cancer data are used to illustrate the procedures.
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