 Estimating Mean Survival Time: When is it Possible?Ying Ding and Bin Nan Scandinavian Journal of Statistics, 2015, vol. 42, issue 2, 397-413 Abstract: type="main" xml:id="sjos12112-abs-0001"> For right-censored survival data, it is well-known that the mean survival time can be consistently estimated when the support of the censoring time contains the support of the survival time. In practice, however, this condition can be easily violated because the follow-up of a study is usually within a finite window. In this article, we show that the mean survival time is still estimable from a linear model when the support of some covariate(s) with non-zero coefficient(s) is unbounded regardless of the length of follow-up. This implies that the mean survival time can be well estimated when the support of linear predictor is wide in practice. The theoretical finding is further verified for finite samples by simulation studies. Simulations also show that, when both models are correctly specified, the linear model yields reasonable mean square prediction errors and outperforms the Cox model, particularly with heavy censoring and short follow-up time. Date: 2015 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:42:y:2015:i:2:p:397-413 Ordering information: This journal article can be ordered from Access Statistics for this article Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association |
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