‘In TBE [theory-based evaluation] practice […] theory as represented is not specific enough to support causal conclusions in inference […]. For example, in contribution analysis “causal assumptions” refer to a “causal package” consisting of the program intervention and a set of contextual conditions that together may explain an observed change in the outcome […]. In realist evaluation, the causal mechanisms that are triggered by the intervention are specified in “configuration” with their context and the outcome. Often, however, the causal structure of the configuration is not clear […]. Moreover, the main TBE approaches to inference do not have standard practices, conventions, for treating bias in evidence […].

‘TBE practitioners may borrow from other methods to test theoretical assumptions […]. Sometimes TBE employs regression analysis or quasi-experimental propensity score matching in inference (our running example in this article of an actual TBE program evaluation does so).’

Schmidt, R. (2024). A graphical method for causal program attribution in theory-based evaluation. Evaluation, online first.