Abstract
Those who report a clinical trial should acknowledge the right of the ‘consumer’ to make decisions based on his own valuation of the beneficial and adverse effects which rival treatments may have. Suppose a new patient is inclined to trade one unit of benefit for c units of complication. Then he should (should not) be given the treatment if his estimated utility gain, χ1 -cχ2, is positive (negative) and statistically significant according to the data of the trial: here χ12) denotes the observed average benefit (complication level). If the estimated gain is not statistically significant, the data do not allow any firm recommendation. This c-dependent recommendation in general cannot be determined from inspection of a joint confidence region for the two means concerned. Therefore investigators should present the outcome of the significance test as a function of c (inverted inference). Typically there are several types of adverse effect or benefit, in which case the quantity c must be generalized into a vector of personal relative utility weights.