The Screening, MOAT study uses the Morris one-step-at-a-time (MOAT) method, which means that in each run, only one input parameter is given a new value. The Screening, MOAT study method first samples the m parameters with the Morris sampling method. For each replication point, the parameter value is perturbed in every parameter dimension, such that r (m+1) total model evaluations are needed. From the evaluated data, this study type can compute the elementary effect for each input parameter and each quantity of interest. From the elementary effect for all the r replication points, you get the MOAT mean and the MOAT standard deviation. The higher the MOAT mean μi, the more sensitive the ith input parameter is. The higher the MOAT standard deviation σi, the more interaction the ith input parameter has with other parameters. More details about the MOAT method and Morris sampling method are described in the theory section under Data Sampling — Morris Sampling and Screening — Morris One-at-a-Time Method, respectively.