Abstract: Supersaturated designs are designed to assess the effects of many factors simultaneously. The assumption of ``effect sparsity'' is often needed to justify the selection of these designs. However, when effect sparsity holds, Type I errors can easily occur. Forward-selection multiple test procedures are proposed to address and solve this problem.
Key words and phrases: Adjusted p-values, control variates, multiplicity adjustment, resampling , variable selection.