Abstract
The long-term survivor mixture model is commonly applied to analyse survival data when some individuals may never experience the failure event of interest. A score test is presented to assess whether the cured proportion is significant to justify the long-term survivor mixture model. Sampling distribution and power of the test statistic are evaluated by simulation studies. The results confirm that the proposed test statistic performs well in finite sample situations. The test procedure is illustrated using a breast cancer survival data set and the clustered multivariate failure times from a multi-centre clinical trial of carcinoma. Copyright © 2009 John Wiley & Sons, Ltd.
| Original language | English |
|---|---|
| Pages (from-to) | 3454-3466 |
| Journal | Statistics in Medicine |
| Volume | 28 |
| Issue number | 27 |
| DOIs | |
| Publication status | Published - 30 Nov 2009 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Keywords
- Cured proportion
- Long-term survivors
- Mixture model
- Random effects
- Score test
Policy Impact
- Cited in Policy Documents
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