  Robust test statistics for the two-way MANOVA based on the minimum covariance
determinant (MCD) estimator are proposed as alternatives to the classical
Wilks' Lambda test statistics which are well known to be very sensitive to
outliers as they are based on classical normal theory estimates of generalized
variances. The classical Wilks' Lambda statistics are robustified by replacing
the classical estimates by highly robust and efficient reweighted MCD
estimates. Further, Monte Carlo simulations are used to evaluate the
performance of the new test statistics under various designs by investigating
their finite sample accuracy, power, and robustness against outliers. Finally,
these robust test statistics are applied to a real data example.
