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Non-parametric Bayesian approach to hazard regression: a case study with a large number of missing covariate values.
| Content Provider | Semantic Scholar |
|---|---|
| Author | Arjas, Elja |
| Copyright Year | 1996 |
| Abstract | A 'packaged' non-parametric multiplicative hazard regression model is proposed, and applied to a study of the effects of some genetic and viral factors in the development of spontaneous leukaemia in mice. Hierarchical modelling and data augmentation are used to deal with the large number of missing covariate values. A Bayesian procedure is adopted, and the Metropolis-Hastings algorithm is used in the numerical computation of the posterior distribution. |
| File Format | PDF HTM / HTML |
| PubMed reference number | 8870158 |
| Journal | Medline |
| Volume Number | 15 |
| Issue Number | 16 |
| Alternate Webpage(s) | https://wiki.helsinki.fi/download/attachments/33902680/arjas%20liu1996,%20nonparamteric.pdf?api=v2&modificationDate=1331154158911&version=1 |
| Alternate Webpage(s) | https://doi.org/10.1002/%28SICI%291097-0258%2819960830%2915%3A16%3C1757%3A%3AAID-SIM336%3E3.0.CO%3B2-J |
| Journal | Statistics in medicine |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |