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Contribution Analysis

Contribution analysis is a theory-based evaluation approach that addresses the attribution problem — establishing whether and how an intervention made a difference — without relying on an experimental counterfactual. Developed by John Mayne from 2001 onward, it works by articulating the program's theory of change, gathering evidence along that chain, and then assembling a 'contribution story' that is progressively stress-tested against rival explanations. The aim is not statistical attribution but a credible, evidence-based conclusion that the program plausibly contributed to observed results, in the face of other influencing factors.

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Sources

  1. Mayne, J. (2012). Contribution analysis: Coming of age? Evaluation, 18(3), 270–280. DOI: 10.1177/1356389012451663
  2. Mayne, J. (2001). Addressing attribution through contribution analysis: Using performance measures sensibly. Canadian Journal of Program Evaluation, 16(1), 1–24. DOI: 10.3138/cjpe.016.001

How to cite this page

ScholarGate. (2026, June 22). Contribution Analysis for Causal Inference in Program Evaluation. ScholarGate. https://scholargate.app/en/public-policy/contribution-analysis

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Referenced by

ScholarGateContribution Analysis (Contribution Analysis for Causal Inference in Program Evaluation). Retrieved 2026-06-24 from https://scholargate.app/en/public-policy/contribution-analysis · Dataset: https://doi.org/10.5281/zenodo.20539026