The analysis for mode effects in the CATI/CAPI Overlap Study has relied heavily on the two sample t-test. This test is popular because it is easily interpretable and fairly robust to the assumption of normality. The latter assumption is, however, difficult to verify with complex survey data. Moreover, the variance estimate used in the parametric analysis is not distributed as a Chi-Squared random variable. Therefore, we apply a variety of nonparametric methods to split panel data from the Basic CPS and Parallel Survey, and show a comparison of the results to the normal theory based results.