Summary: The topic of this work is an extension of our previous work [J. Appl. Stat. 32, No. 10; 1051–1066 (2005; Zbl 1121.62300)] on robust \(2^k\) factorial designs with Weibull error distributions. We obtain robust and efficient estimators of the parameters in \(2^k\) factorial designs by using the methodology known as modified maximum likelihood (MML) and propose new test statistics based on MML estimators for testing the main effects and the interactions when the distributions of the error terms are generalized logistic. We show that the proposed test statistics are more powerful and robust than the traditional test statistics based on the least squares (LS) estimators.