Combining components of quality of life to increase precision and evaluate trade-offs
| Autor: | R. J. Simes, Thomas Lumley, Val Gebski, H. M. Hudson |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Statistics and Probability
Biometry Multivariate analysis Epidemiology Breast Neoplasms Machine learning computer.software_genre Bias Quality of life Multiple time dimensions Antineoplastic Combined Chemotherapy Protocols Linear regression Humans Medicine Clinical Trials as Topic Measure (data warehouse) business.industry Megestrol Acetate Linear model Weighting Data Interpretation Statistical Multivariate Analysis Linear Models Quality of Life Female Artificial intelligence business Telecommunications computer Curse of dimensionality |
| Zdroj: | Statistics in Medicine. 20:3231-3249 |
| ISSN: | 1097-0258 0277-6715 |
| DOI: | 10.1002/sim.1035 |
| Popis: | Methods for combining measurements on multiple dimensions of quality of life can reduce the dimensionality of the data and increase the precision of estimation. When the dimensions are weighted according to their importance to patients, the resulting estimate is clinically useful and provides a step towards a true utility estimate. We derive two such weighting methods using linear regression on a measure of overall quality of life and demonstrate their usefulness in the analysis of quality of life data from two clinical trials of cancer therapies. Procedures for transforming the quality of life measures into utility measures are demonstrated. |
| Databáze: | OpenAIRE |
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