Evaluating human-robot social interactions in a rigorous manner is notoriously difficult: studies are either conducted in labs with constrained protocols to allow for robust measurements and a degree of replicability, but at the cost of ecological validity; or in the wild, which leads to superior experimental realism, but often with limited replicability and at the expense of rigorous interacti...

We show that publishing results using the statistical significance filter—publishing only when the p-value is less than 0.05—leads to a vicious cycle of overoptimistic expectation of the replicability of results. First, we show analytically that when true statistical power is relatively low, computing power based on statistically significant results will lead to overestimates of power. Then, we...

In cancer research, clustering techniques are widely used for exploratory analyses and dimensionality reduction, playing a critical role in the identification of novel subtypes, often with direct implications patient management. As data collected by multiple research groups grows, it is increasingly feasible to investigate replicability procedures, that is, their ability consistently recover bi...

In this paper, we propose definitions for a general, domain-independent concept of replicability and specifically focus on the notion of self-replication. We argue that selfreplication should not be viewed as a binary property of a system, but rather as a continuously valued property of the interaction between a system and its environment. This property, selfreplicability, represents the effect...