Editing Selection bias (section)

==Mitigation==
In the general case, selection biases cannot be overcome with statistical analysis of existing data alone, though [[Heckman correction]] may be used in special cases. An assessment of the degree of selection bias can be made by examining correlations between [[exogenous]] (background) variables and a treatment indicator. However, in [[regression analysis|regression]] models, it is correlation between ''unobserved'' determinants of the outcome and ''unobserved'' determinants of selection into the sample which bias estimates, and this correlation between unobservables cannot be directly assessed by the observed determinants of treatment.<ref>{{Cite journal | doi = 10.2307/1912352| jstor = 1912352| title = Sample Selection Bias as a Specification Error| journal = Econometrica| volume = 47| issue = 1| pages = 153–161| year = 1979| last1 = Heckman | first1 = J. J. }}</ref>

When data are selected for fitting or forecast purposes, a coalitional game can be set up so that a fitting or forecast accuracy function can be defined on all subsets of the data variables.