Collective wisdom: Methods of confidence interval aggregation
Aidan Lyon, Bonnie C Wintle, Mark Burgman
JOURNAL OF BUSINESS RESEARCH | ELSEVIER SCIENCE INC | Published : 2015
We report the results of a meta-analysis study of the relative accuracies for a range of methods for aggregating confidence interval estimates of unknown quantities. We found that a simple "trim-and-average" method-that is, remove outliers and then average-produced the most accurate estimates. Our results show that more complicated methods of confidence interval aggregation, which factor in confidence levels and estimate imprecisions, do not produce estimates more accurate than those produced by the simple trim-and-average method.
Aidan Lyon acknowledges support from the Munich Centre for Mathematical Philosophy, the Alexander van Humboldt Foundation, and the Centre of Excellence for Biosecurity Risk Analysis. Bonnie Wintle was supported by the National Environmental Research Program (NERP) Environmental Decisions Hub.