Robustness tests emerged as social scientists’ response to the uncertainty they face in specifying empirical models. We argue that the logic of robustness testing warrants a fundamental change in how researchers make inferences in their analysis of observational data. The dominant conception of robustness, which assesses whether the estimated effects remain statistically significant in all robu...

Kriging or Gaussian process models are popular metamodels (surrogate emulators) of simulation models; these give predictors for input combinations that not simulated. To validate computationally expensive models, the analysts often apply efficient cross-validation. In this paper, we derive new statistical tests so-called leave-one-out Graphically, present as scatterplots augmented with confiden...