Cryptic population structure can increase both type I and type II errors. This is particularly problematic in case-control association studies of unrelated individuals. Some researchers believe that these problems are obviated in families. We argue here that this may not be the case, especially if families are drawn from a known admixed population such as Mexican Americans. We use a principal component approach to evaluate and visualize the results of three different approaches to searching for cryptic structure in the 20 multigenerational families of the Genetic Analysis Workshop 18 (GAW18). Approach 1 uses all family members in the sample to identify what might be considered «outlier» kindreds. Because families are likely to differ in size (in the GAW18 families, there is about a 4-fold difference in the number of typed individuals), approach 2 uses a weighting system that equalizes pedigree size. Approach 3 concentrates on the founders and the «marry-ins» because, in principle, the entire pedigree can be reconstructed with knowledge of the sequence of these unrelated individuals and genome-wide association study (GWAS) data on everyone else (to identify the position of recombinations). We demonstrate that these three approaches can yield very different insights about cryptic structure in a sample of families.