When the maximum amount allowable under a limitation is less than the total amount determined in accordance with the principles in this part, the amount not recoverable under the Federal award may not be charged to the Federal award. (a) The Federal agency or pass-through entity must provide to the non-Federal entity a notice of termination. Only under extraordinary and rare circumstances would 5 2 Prepare A Post such access include review of the true name of victims of a crime. Routine monitoring cannot be considered extraordinary and rare circumstances that would necessitate access to this information. When access to the true name of victims of a crime is necessary, appropriate steps to protect this sensitive information must be taken by both the non-Federal entity and the Federal awarding agency.
(a) See § 200.1 for the definitions of capital expenditures, equipment, special purpose equipment, general purpose equipment, acquisition cost, and capital assets. (2) Specific written direction of an authorized official of the Federal awarding agency. (D) A final decision by an appropriate Federal official to debar or suspend the non-Federal entity, to rescind or void a Federal award, or to terminate a Federal award by reason of a violation or failure to comply with a statute, regulation, or the terms and conditions of the Federal award. (3) Amounts funded in excess of the actuarially determined amount for a fiscal year may be used as the non-Federal entity contribution in a future period.
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Where sensitivity analyses identify particular decisions or missing information that greatly influence the findings of the review, greater resources can be deployed to try and resolve uncertainties and obtain extra information, possibly through contacting trial authors and obtaining individual participant data. If this cannot be achieved, the results must be interpreted with an appropriate degree of caution. Such findings may generate proposals for further investigations and future research. Review authors may undertake sensitivity analyses to assess the potential impact of missing outcome data, based on assumptions about the relationship between missingness in the outcome and its true value. For dichotomous outcomes, Higgins and colleagues propose a strategy involving different assumptions about how the risk of the event among the missing participants differs from the risk of the event among the observed participants, taking account of uncertainty introduced by the assumptions (Higgins et al 2008a).
