the estimation of the extrapolation to ate from the late requires certain key assumptions, which may vary from one approach to another. while some may assume homogeneity within covariates, and thus extrapolate based on strata, others may instead assume monotonicity.  all will assume the absence of defiers within the experimental population. some of these assumptions may be weaker than others—for example, the monotonicity assumption is weaker than the ignorability assumption. however, there are other trade-offs to consider, such as whether the estimates produced are point-estimates, or bounds. ultimately, the literature on generalizing the late relies entirely on key assumptions. it is not a design-based approach per se, and the field of experiments is not usually in the habit of comparing groups unless they are randomly assigned. even in case when assumptions are difficult to verify, researcher can incorporate through the foundation of experiment design. for example, in a typical field experiment where instrument is  “encouragement to treatment”, treatment heterogeneity could be detected by varying intensity of encouragement. if the compliance rate remains stable under different intensity, if could be a signal of homogeneity across groups. thus, it is important to be a smart consumer of this line of literature, and examine whether the key assumptions are going to be valid in each experimental case.