The dissection of complex traits frequently calls for multiple analyses to be performed, including the use of both multiple phenotypes and genetic models. These multiple phenotypes and models are often not independent, and hence the necessary correction for the multiple testing is not straightforward. In this paper we offer a new approach to address the problem of how to correct for non-independent multiple analyses in genomewide linkage studies. We describe one method of how to determine the number of ‘effectively independent’ tests performed in a linkage study using simple linear regression techniques. Further we describe how to use such information to establish genomewide significance thresholds for infinitely dense genomewide maps.