Abstract
The mean residual life (MRL) measures the remaining life expectancy and is useful in actuarial studies, biological experiments and clinical trials. To assess the covariate effect, an additive MRL regression model has been proposed in the literature. In this paper, we focus on the topic of model checking. Specifically, we develop two goodness-of-fit tests to test the additive MRL model assumption. We explore the large sample properties of the test statistics and show that both of them are based on asymptotic Gaussian processes so that resampling approaches can be applied to find the rejection regions. Simulation studies indicate that our methods work reasonably well for sample sizes ranging from 50 to 200. Two empirical data sets are analyzed to illustrate the approaches.
| Original language | English |
|---|---|
| Pages (from-to) | 385-408 |
| Number of pages | 24 |
| Journal | Lifetime Data Analysis |
| Volume | 16 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Jul 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Additive mean residual life model
- Gaussian process
- Goodness-of-fit test
- Right-censored survival data
ASJC Scopus subject areas
- Applied Mathematics
- General Medicine
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