Analytical generalisation involves making projections about the likely transferability of findings from an evaluation, based on a theoretical analysis of the factors producing outcomes and the effect of context. Realist evaluation can be particularly important for this.
Analytic generalisation is distinct from statistical generalisation, in that it does not draw inferences from data to a population. Instead, analytic generalisation compares the results of a case study to a previously developed theory.
"A ... common concern about case studies is that they provide little basis for scientific generalization. "How can you generalize from a single case?" is a frequently heard question. ... In fact, scientific facts are rarely based on single experiments; they are usually based on a multiple set of experiments that have replicated-the same phenomenon under different conditions. The same approach can be used with multiple-case studies but requires a different concept of the appropriate research designs ... The short answer is that case studies, like experiments, are generalizable to theoretical propositions and not to populations or universes. In this sense, the case study, like the experiment, does not represent a "sample," and in doing a case study, your goal will be to expand and generalize theories (analytic generalization) and not to enumerate frequencies (statistical generalization)." (Yin, 2009: 15)
In the Encyclopedia of Case Study Research, Robert Yin describes the process of analytic generalisation as a two-step process: First, a conceptual claim is made by researchers which "show[s] how their case study findings bear upon a particular theory, theoretical construct, or theoretical ... sequence of events". Secondly, this theory is applied to implicate situations in which similar events might occur. (Yin, 2010)
(From Yin, 2010)
- The argument or theory should be made clear at the beginning of the case study
- The argument should be grounded in a research literature rather than specific related to the case study
- Findings should show how the results of the case study either challenged or supported the theory or argument
- If the findings support the theory, a logical and sound argument needs to be made by researchers to show how these findings can be generalised to similar situations.
- Examining rival hypotheses will strengthen claims of analytical generalisation
- "Beyond making a claim, the generalizability of the findings from a single case study increases immeasurably if similar results have been found with other case studies—whether such studies already existed in the literature or were completed after the first case study." (Yin, 2010)
Encyclopedia of Case Study Research: Analytic Generalization: Robert Yin gives a clear overview of analytic generalisation from case studies, where it is appropriate, and how to effectively apply it.
Case Study Research: Design and Methods: The fifth edition of Robert Yin's bestselling book on case studies has an expanded section an analytic generalisation.
Yin, R. (1994) Case Study Research: Design and Methods. Sage Publications, Thousand Oaks, CA.
Yin, R. (2010). 'Analytic Generalization.' In Albert J. Mills, G. Durepos, & E. Wiebe (Eds.), Encyclopedia of Case Study Research. (pp. 21-23). Thousand Oaks, CA: SAGE Publications, Inc.