Biomedical Engineering Reference
In-Depth Information
Li
95
gave a detailed review of the proportional odds regression model.
It is commonly seen in survival analysis that estimated survival curves
level o at a nonzero value after a certain time, even when many individ-
uals are followed beyond that time. This type of data has heavy censoring
at the end of the follow-up period. One can regard the population as con-
sisting of two groups: individuals who are not susceptible to an event of
interest, and individuals who are susceptible to the event if they are fol-
lowed long enough. A number of parametric and semiparametric cure (or
mixture) models for this type of heavily censored data have been proposed
by Farewell
51
, Yamaguchi
156
, Kuk and Chen
86
, Taylor
139
, Chen, Ibrahim,
and Sinha
30
, Sy and Taylor
134
, Peng and Dear
111
, and Li and Taylor
93;94
.
See [98] for a detailed introduction to cure models. Li, Taylor, and Sy
92
systematically studied the identiability of cure models. Finally, see [104]
for a detailed review of statistical methodologies used in survival analysis
that were not discussed in this chapter.
Acknowledgments
This work was partially supported by Cancer Center Support Grant
CA21765 from the National Institutes of Health and by the American
Lebanese Syrian Associated Charities (ALSAC).
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