Conventional clinical trials involve tests of hypotheses with statistics computed from values of dependent variables alone. An alternative is to test hypotheses with statistics computed from benefit/harm scores that measure longitudinal associations between dose and values of the dependent variables. The proposed standardized measure of benefit/harm quantifies the strength of evidence that a patient did either better or worse while on treatment. A benefit/harm score, particularly when obtained from a randomized, N-of-1 trial, indicates a beneficial or harmful treatment effect for the individual. Benefit/harm scores from samples of patients are evaluated with standard statistical tests, with or without group comparisons, to make inferences about populations. The proposed alternative strategy can yield within-patient indicators of treatment effect that are more reliable, valid, comprehensive, and detailed. This, in turn, could help make many population-based clinical trials more informative, cost-effective, and clinically useful for participants.