Several methods for formal analysis of unreplicated factorial type experiments have been proposed in the literature. Based on a simulation study, five formal methods found in the literature based on the effect sparsity principle have been studied. The simulation included 23 and 24 type factorials with one, two, or four active effects. The simulated signal-to-noise ratios for the effects were all between two and four, and the Type I and Type II errors of the analysis methods were analysed. Preliminary results show that Bayesian models are more powerful in these contexts, especially if informative priors based on the effect heredity and effect hierarchy principles are used.