This paper develops a broad theme about policy choice under ambiguity through study of a particular decision criterion. The broad theme is that, where feasible, choice between a status quo policy and an innovation is better framed as selection of a treatment allocation than as a binary decision....

The original research papers collected in this volume continue the development of discrete choice analysis, of related structural models for analysis of choice behavior, and of the statistical theory used in inference on these models. Most papers in the volume are revised versions of ones...

This paper extends my research applying statistical decision theory to treatment choice with sample data, using maximum regret to evaluate the performance of treatment rules. The specific new contribution is to study as-if optimization using estimates of illness probabilities in clinical choice...

"Although uncertainty is common in patient care, it has not been largely addressed in research on evidence-based medicine. Patient Care Under Uncertainty strives to correct this huge omission. For the past few years, renowned economist Charles Manski has been applying the statistical tools of...

The Wald development of statistical decision theory addresses decision making with sample data. Wald's concept of a statistical decision function (SDF) embraces all mappings of the form [data → decision]. An SDF need not perform statistical inference; that is, it need not use data to draw...

This paper modifies the Wald development of statistical decision theory to offer new perspective on the performance of certain statistical treatment rules. We study the quantile performance of test rules, ones that use the outcomes of hypothesis tests to allocate a population to two treatments....