A modern, decision-theoretic framework can help clarify important practical questions of experimental design. Building on our recent work, this chapter begins by summarizing our framework for understanding the goals of experimenters and applying this to rerandomization. We then use this...

This chapter reviews developments in the theory of decision making under risk and uncertainty, focusing on models that, over the last 40 years, dominated the theoretical discussions. It also surveys some implications of the departures from the “linearity in the probabilities” aspect of...

The phenomena of ambiguity and ambiguity aversion , introduced in Daniel Ellsberg’s seminal 1961 article, are ubiquitous in the real world and violate both the key rationality axioms and classic models of choice under uncertainty. In particular, they violate the hypothesis that individuals’...

Bayesian decisions are observationally identical to decisions with judgment. Decisions with judgment test whether a judgmental decision is optimal and, in case of rejection, move to the closest boundary of the confidence interval, for a given confidence level. The resulting decisions condition...