Competing risks models and time-dependent covariates
New statistical models for analysing survival data in an intensive care unit context have recently been developed. Two models that offer significant advantages over standard survival analyses are competing risks models and multistate models. Wolkewitz and colleagues used a competing risks model to examine survival times for nosocomial pneumonia and mortality. Their model was able to incorporate time-dependent covariates and so examine how risk factors that changed with time affected the chances of infection or death. We briefly explain how an alternative modelling technique (using logistic regression) can more fully exploit time-dependent covariates for this type of data.
Impact and interest:
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Journal Article|
|Keywords:||Healthcare acquired infections, Statistical modelling|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Applied Statistics (010401)|
Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > MEDICAL MICROBIOLOGY (110800) > Medical Infection Agents (incl. Prions) (110802)
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Health|
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Public Health & Social Work
|Deposited On:||30 Apr 2009 15:33|
|Last Modified:||09 Jun 2010 23:27|
Repository Staff Only: item control page