Módszerek összehasonlítása

	Summative Evaluation	Impact Evaluation Design
Tudományterület	Public Policy	Public Policy
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	1967	2016
Megalkotó	Michael Scriven	Development and program-evaluation community; codified by Gertler et al. (World Bank)
Típus	Judgement-oriented evaluation function	Design framework for causal impact evaluation
Alapmű	Scriven, M. (1967). The methodology of evaluation. In R. W. Tyler, R. M. Gagné, & M. Scriven (Eds.), Perspectives of Curriculum Evaluation (pp. 39–83). Chicago: Rand McNally. ISBN: 9780528616600	Gertler, P. J., Martinez, S., Premand, P., Rawlings, L. B., & Vermeersch, C. M. J. (2016). Impact Evaluation in Practice (2nd ed.). Washington, DC: World Bank. ISBN: 9781464807794
Alternatív nevek	Outcome Judgement Evaluation, Accountability Evaluation	Impact Evaluation, Causal Impact Evaluation Design, Counterfactual Evaluation Design
Kapcsolódó	4	3
Összefoglaló	Summative evaluation is evaluation conducted to render an overall judgement of a program, policy or product — its merit, worth, effectiveness or impact — typically after it has been implemented or has matured. Named by Michael Scriven in his 1967 essay 'The Methodology of Evaluation' as the counterpart to formative evaluation, its purpose is to inform consequential decisions: whether to continue, expand, replicate, defund or certify an intervention. It addresses the bottom-line question 'did it work, and was it worth it?' for audiences such as funders, policymakers and the public.	Impact evaluation design is the upstream task of structuring an evaluation so that it can credibly attribute changes in outcomes to a policy or program rather than to other factors. Its defining concern is the counterfactual: what would have happened to participants in the absence of the intervention. Codified in resources such as the World Bank's Impact Evaluation in Practice, the design process selects an identification strategy — randomised assignment, or a quasi-experimental method such as difference-in-differences, regression discontinuity, instrumental variables or matching — that constructs a valid comparison and yields an unbiased estimate of the intervention's effect.