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In genome wide association studies (GWAS), families based studies tend to have less power to detect genetic associations than population based studies, such as case-control studies. This can be an issue when testing if genes in a family based GWAS have a direct effect on the phenotype of interest or if the genes act indirectly through a secondary phenotype. When multiple SNPs are tested for a direct effect in the family based study, a screening step can be used to minimize the burden of multiple comparisons in the causal analysis. We propose a 2-stage screening step that can be incorporated into the family based association test (FBAT) approach similar to the conditional mean model approach in the VanSteen-algorithm [1]. Simulations demonstrate that the type 1 error is preserved and this method is advantageous when multiple markers are tested. This method is illustrated by an application to the Framingham Heart Study.