University of Limerick Institutional Repository
Modelling high dimensional sets of binary co-morbidities
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| dc.contributor.author | Conde, Susana | |
| dc.contributor.author | MacKenzie, Gilbert | |
| dc.date.accessioned | 2013-01-08T15:00:39Z | |
| dc.date.available | 2013-01-08T15:00:39Z | |
| dc.date.issued | 2007 | |
| dc.identifier.uri | http://hdl.handle.net/10344/2791 | |
| dc.description | peer-reviewed | en_US |
| dc.description.abstract | The construction of classical co-morbidity indices is described. When the co-morbidities are binary we advocate the use of log-linear models which better capture the dependence structure in the data. We use R to implement new search strategies which enable us to analyse, sparse, high dimensional contingency tables rapidly and hence identify the best fitting models. We apply our new algorithms to a set of real medical data. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | IWSM | en_US |
| dc.relation.ispartofseries | Proceedings of the 22nd International Workshop on Statistical Modelling; | |
| dc.relation.uri | http://www.statmod.org/workshops.htm | |
| dc.subject | co-morbidity index | en_US |
| dc.subject | binary data | en_US |
| dc.subject | hierarchical long-linear model | en_US |
| dc.title | Modelling high dimensional sets of binary co-morbidities | en_US |
| dc.type | info:eu-repo/semantics/conferenceObject | en_US |
| dc.type.supercollection | all_ul_research | en_US |
| dc.type.supercollection | ul_published_reviewed | en_US |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | en_US |
| dc.internal.rssid | 1399830 |
