In studies of association between genetic markers and a disease, the transmission disequilibrium test (TDT) has become a standard procedure. It was introduced originally as a test for linkage in the presence of association and can be used as a test for association under appropriate assumptions. The power of the TDT test for association between a candidate gene and disease depends on the underlying genetic model and the TDT is the optimal test if the additive model holds. Related methods have been obtained for a given mode of inheritance (e.g. dominant or recessive). Quite often, however, the true model is unknown and selection of a single method of analysis is problematic, since use of a test optimal for one genetic model usually leads to a substantial loss of power if another genetic model is the true one. The general approach of efficiency robustness has suggested two types of robust procedures, which we apply to TDT-type association tests. When the plausible range of alternative models is wide (e.g. dominant through recessive) our results indicate that the maximum (MAX) of several test statistics, each of which is optimal for quite different models, has good power under all genetic models. In situations where the set of possible models can be narrowed (e.g. dominant through additive) a simple linear combination also performs well. In general, the MAX has better power properties than the TDT for the study of candidate genes when the mode of inheritance is unknown.