  In the field of road safety, it is common to use responsibility analyses to
assess the effect of a given factor on the risk of being responsible for an
accident, among drivers involved in an accident only. Even if this design is
now widely adopted in the field, the question of selection bias is often
raised. The structural Causal Model framework now provides valuable tools to
assess causal effects from observational data and identify selection bias. In
this article, we briefly review recent results regarding the recoverability of
causal effects from selection biased data, and apply them to the case of
responsibility analyses. Our objective is to formally determine whether causal
effects can be unbiasedly estimated through this type of analyses, when
available data are restricted to severe accidents, as it is commonly the case
in practice. However, because speed has a direct effect on the severity of the
accident, we show that causal odds-ratios are not estimable from responsibility
analyses. We present numerical results to illustrate our argument, the
magnitude of the bias and to discuss recent results from real data.
