Matching of cases and controls can eliminate the matched parameter as a cause of difference. Controls are matched to cases on the basis of certain characteristics, which are also known to be present in the cases. The purpose is to eliminate confounding variables (factors in addition to the risk factor that influence whether disease occurs). If such confounding factors are unevenly distributed between study groups, they can distort comparsions and the conclusions being made. Age is a common confounder (standardisation can be used). Matching should be used sparingly. The tendency is to match in analysis of results rather than in the design stage. Overmatching occurs if a variable matched could, in fact be an intermediate on a casual pathway. This would mask a disease association.