Selection of covariates is among the most controversial and difficult tasks in epidemiologic analysis. Correct variable selection addresses the problem of confounding in etiologic research and allows unbiased estimation of probabilities in prognostic studies. The aim of this commentary is to assess how often different variable selection techniques were applied in contemporary epidemiologic analysis. It was of particular interest to see whether modern methods such as shrinkage or penalized regression were used in recent publications. Stepwise selection methods remained the predominant method for variable selection in publications in epidemiological journals in 2008. Shrinkage methods were not used in any of the reviewed articles. Editors, reviewers and authors have insufficiently promoted the new, less controversial approaches of variable selection in the biomedical literature, whereas statisticians may not have adequately addressed the method's feasibility.

Additional Metadata
Keywords Confounding, Covariates, Etiology, Lasso, Prediction, Shrinkage, Stepwise, Variable selection
Persistent URL dx.doi.org/10.1007/s10654-009-9411-2, hdl.handle.net/1765/25691
Citation
Walter, S., & Tiemeier, H.W.. (2009). Variable selection: Current practice in epidemiological studies. European Journal of Epidemiology, 24(12), 733–736. doi:10.1007/s10654-009-9411-2