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Performance of Disease Risk Scores, Propensity Scores, and Traditional Multivariable Outcome Regression in the Presence of Multiple Confounders
- Source :
- American Journal of Epidemiology. 174:613-620
- Publication Year :
- 2011
- Publisher :
- Oxford University Press (OUP), 2011.
-
Abstract
- Propensity scores are widely used in cohort studies to improve performance of regression models when considering large numbers of covariates. Another type of summary score, the disease risk score (DRS), which estimates disease probability conditional on nonexposure, has also been suggested. However, little is known about how it compares with propensity scores. Monte Carlo simulations were conducted comparing regression models using the DRS and the propensity score with models that directly adjust for all of the individual covariates. The DRS was calculated in 2 ways: from the unexposed population and from the full cohort. Compared with traditional multivariable outcome regression models, all 3 summary scores had comparable performance for moderate correlation between exposure and covariates and, for strong correlation, the full-cohort DRS and propensity score had comparable performance. When traditional methods had model misspecification, propensity scores and the full-cohort DRS had superior performance. All 4 models were affected by the number of events per covariate, with propensity scores and traditional multivariable outcome regression least affected. These data suggest that, for cohort studies for which covariates are not highly correlated with exposure, the DRS, particularly that calculated from the full cohort, is a useful tool.
- Subjects :
- Multivariate analysis
Epidemiology
business.industry
Confounding
Confounding Factors, Epidemiologic
Regression analysis
Prognosis
Cohort Studies
Logistic Models
Standard error
Bias
Multivariate Analysis
Cohort
Covariate
Propensity score matching
Humans
Medicine
Epidemiologic Methods
Propensity Score
business
Probability
Cohort study
Demography
Subjects
Details
- ISSN :
- 14766256 and 00029262
- Volume :
- 174
- Database :
- OpenAIRE
- Journal :
- American Journal of Epidemiology
- Accession number :
- edsair.doi.dedup.....0ab9038c7e60d7258c6d98024f0122b6