In essence, meta-analysis is a statistical method to create a single estimate of effects from multiple studies with conflicting results. For example, a drug regulator considering approval of a painkiller may review 20 studies, 5 of which show negative side effects and 15 of which don’t. Meta-analysis aggregates findings from across the studies and informs the regulator’s decision about whether the drug needs a warning label.
When combined with local cost data, meta-analysis allows PFS partners to share a more precise estimate of expected effects while constructing the project. An example of meta-analysis in practice for social programs is the cost-benefit analysis tool developed by the Urban Institute for the District of Columbia Crime Policy Institute.