Aleatory Sovereignty and the Rule of Sensitive Spaces

Addressing life in borders and refugee camps requires understanding the way these spaces are ruled, the kinds of problems rule poses for the people who live there, and the abilities of inhabitants to remake their own lives. Recent literature on such spaces has been influenced by Agamben's notion of sovereignty, which reduces these spaces and their residents to abstractions. We propose an alternate framework focused on what we call aleatory sovereignty, or rule by chance. This allows us to see camps and borders not only as the outcomes of humanitarian projects but also of anxieties about governance and rule; to see their inhabitants not only as abject recipients of aid, but also as individuals who make decisions and choices in complex conditions; and to show that while the outcome of projects within such spaces is often unpredictable, the assumptions that undergird such projects create regular cycles of implementation and failure.

A NOVEL AND SIMPLE RULE OF THUMB FOR MULTIPLICITY CONTROL IN EQUIVALENCE TESTING USING TWO ONE-SIDED TESTS

Equivalence testing is growing in use in scientific research outside of its traditional role in the drug approval process. Largely due to its ease of use and recommendation from the United States Food and Drug Administration guidance, the most common statistical method for testing (bio)equivalence is the two one-sided tests procedure (TOST). Like classical point-null hypothesis testing, TOST is subject to multiplicity concerns as more comparisons are made. In this manuscript, a condition that bounds the family-wise error rate (FWER) using TOST is given. This condition then leads to a simple solution for controlling the FWER. Specifically, we demonstrate that if all pairwise comparisons of k independent groups are being evaluated for equivalence, then simply scaling the nominal Type I error rate down by (k - 1) is sufficient to maintain the family-wise error rate at the desired value or less. The resulting rule is much less conservative than the equally simple Bonferroni correction. An example of equivalence testing in a non drug-development setting is given.