Variable selection for marginal longitudinal models
| dc.contributor.author | Kaigoya, J N | |
| dc.date.accessioned | 2013-05-22T07:30:45Z | |
| dc.date.available | 2013-05-22T07:30:45Z | |
| dc.date.issued | 2006 | |
| dc.identifier.citation | Masters of Science in Mathematical Statistics | en |
| dc.identifier.uri | http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/24335 | |
| dc.description.abstract | Model selection is an essential part of any statistical analysis. A generalized version of Mallows's Cp (GCp) (Cantoni et al., 2005) was developed as a model selection criterion for longitudinal data. GCp, just like Mallows's Cp (Mallows, 1973), provides an estimate of a measure of a model's adequacy for prediction. In this study, the performance of GCp is compared with that of Cp by using longitudinal data of 137 urinary incontinent elderly patients from 38 medical practices | en |
| dc.description.sponsorship | University of Nairobi | en |
| dc.language.iso | en | en |
| dc.title | Variable selection for marginal longitudinal models | en |
| dc.type | Thesis | en |
Files in this item
| Files | Size | Format | View |
|---|---|---|---|
|
There are no files associated with this item. |
|||