Control for confounding is crucial in causal observational studies. However, the modelling of continuous confounders has not received much attention. This is probably because in causal research the ...

2 Swiss Laboratory for Doping Analyses, University Center of Legal Medicine, Geneva and Lausanne, Epalinges, Switzerland Correspondence to Dr Norbert Baume, Swiss Laboratory for Doping Analyses, ...

Multiple regression models are commonly used to control for confounding in epidemiologic research. Parametric regression models, such as multiple logistic regression, are powerful tools to control for ...

Unmeasured confounding variables are a common problem in drawing causal inferences in observational studies. A theorem is given which in certain circumstances allows the researcher to draw conclusions ...