Ray Pawson, one of the originators of realist evaluation was "initially impressed" by how critical realism explains generative causation in experimental science; however, he later criticised its "philosophical grandstanding" and "explain-all Marxism".
[3][4][5] Realist evaluation techniques recognise that there are many interwoven variables operative at different levels in society, thus this evaluation method suits complex social interventions, rather than traditional cause-effect, non-contextual methods of analysis.
This realist technique acknowledges that intervention programmes and policy changes do not necessarily work for everyone, since people are different and are embedded in different contexts.
[8] All research methods are applicable in realist evaluations, according to Pawson and Tilley (1997):[9] "... it is quite possible to carry out realistic evaluation using: strategies, quantitative and qualitative; timescales, contemporaneous or historical; viewpoints, cross-sectional or longitudinal; samples, large or small; goals, action-oriented or audit-centred; and so on and so forth.
"A 2024 book argues that it is possible to run realist randomized controlled trials[10] and Gill Westhorp and Simon Feeny (2024) explain the relevance of surveys and regression models (including interaction terms and covariate adjustment) to testing Context-Mechanism-Outcome configurations.