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Le laboratoire SPHERE (methodS for Patients-centered outcomes and HEalth REsearch, INSERM UMR 1246, Université de NantesUniversité de Tours) et la société IDBC (groupe A2com) ont décidé de créer ensemble le Laboratoire Commun RISCA (Research in Informatics and Statistics for Cohort-based Analyses)

 

Tutorials : overfitting & overadjustment

Home >  Tutorials > Overfitting

A confounder must be a cause of exposure. The adjustement on a consequence of the exposure would result in under-estimating the true causal effect of exposure.

Covariates on the pathway

A too complex model

When the number of events is too low compared to the number of adjustment variables, we consider a possible overfitting. An approximate rule to avoid overfitting is to have at least 10 events per covariate whether for a logistic (Peduzzi et al. 1996) or a Cox (Peduzzi et al. 1995) model.