Two-sample rank tests under complex sampling

Rank tests are widely used for exploratory and formal inference in the health and social sciences. With the widespread use of data from complex survey samples in medical and social research, there is increasing demand for versions of rank tests that account for the sampling design. We propose a general approach to constructing design-based rank tests when comparing groups within a complex sample and when using a national survey as a reference distribution, and illustrate both scenarios with examples. We show that the tests have asymptotically correct levels and that the relative power of different rank tests is not greatly affected by complex sampling. Copyright 2013, Oxford University Press.