mlpwr

We implement a surrogate modeling algorithm to guide simulation-based sample size planning. The method is described in detail in a recent preprint (Zimmer & Debelak (2022) doi:10.31234/osf.io/tnhb2). It supports multiple study design parameters and optimization with respect to a cost function. It can find optimal designs that correspond to a desired statistical power or that fulfill a cost constraint.