Developing a goodness of fit test for a joint model of clustered survival and count data
| dc.contributor.author | Adikari, N. | |
| dc.contributor.author | Sooriyarachchi, M.R. | |
| dc.date.accessioned | 2021-07-07T03:24:20Z | |
| dc.date.available | 2021-07-07T03:24:20Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Mixed responses within clusters are becoming an increasingly popular phenomenon. However, this scenario is a complex one. This research is based on survival and count response data which occur frequently in medical studies. In the literature, there is no satisfactory goodness of fit test for a joint model of these two responses within a cluster setting. Therefore, the main objective of this study is to develop a GOF test for this scenario. Simulation studies were used to examine the type I error rate and the power of the test. An example was used to display the practicality of the test. | en_US |
| dc.description.sponsorship | No Sponsors | en_US |
| dc.identifier.citation | A. P. N. G. Adhikari & M. R. Sooriyarachchi (2020): Developing a goodness of fit test for a joint model of clustered survival and count data, Communications in Statistics - Simulation and Computation, DOI: 10.1080/03610918.2020.1825738 | en_US |
| dc.identifier.uri | http://archive.cmb.ac.lk/handle/70130/5455 | |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor and Francis | en_US |
| dc.subject | Count; Hierarchical data structure; Joint model; Mixed responses; Simulation; Survival | en_US |
| dc.title | Developing a goodness of fit test for a joint model of clustered survival and count data | en_US |
| dc.type | Article | en_US |
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