Compare methods

	Theory of Change Evaluation	Contribution Analysis
Field	Public Policy	Public Policy
Family	Process / pipeline	Process / pipeline
Year of origin	1995	2001
Originator	Carol Weiss; Connell & Kubisch; Funnell & Rogers	John Mayne
Type	Theory-based program evaluation framework	Theory-based approach to causal inference about contribution
Seminal source	Weiss, C. H. (1995). Nothing as practical as good theory: Exploring theory-based evaluation for comprehensive community initiatives for children and families. In J. P. Connell, A. C. Kubisch, L. B. Schorr, & C. H. Weiss (Eds.), New Approaches to Evaluating Community Initiatives: Concepts, Methods, and Contexts (pp. 65–92). Washington, DC: The Aspen Institute. ISBN: 9780898431674	Mayne, J. (2012). Contribution analysis: Coming of age? Evaluation, 18(3), 270–280.
Aliases	Theory-Based Evaluation, ToC Evaluation, Theory-of-Change Approach, Outcomes Pathway Evaluation	Mayne's Contribution Analysis, Contribution Story Analysis, Theory-Based Contribution Analysis
Related	3	3
Summary	Theory of change evaluation is a theory-based approach that evaluates a program against an explicit map of how and why it is expected to produce its intended outcomes. Rooted in Carol Weiss's work on theory-based evaluation and the Aspen Institute's community-initiatives projects of the 1990s, it requires evaluators to articulate the full causal pathway from activities through short- and intermediate-term outcomes to a long-term goal, make the underlying assumptions explicit, and then collect evidence to test whether each link in that chain holds in practice. The theory of change serves simultaneously as a planning tool and as the framework against which the program's progress and plausibility are judged.	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.