Table 2.

Plausibility study design strengths, limitations, and assumptions

Strengths	Limitations	Key assumptions
Intervention group serves as its own control over time	No true counterfactual, so cause and effect cannot be conclusively inferred	Program is preexisting or full (above threshold) coverage
No need to exclude any population or group from the intervention/program, so can be applied to programs with nation-wide coverage	Multiple sources of data, analyses, and triangulations needed to establish plausible impact	Pretest (baseline) data for the relevant indicators can serve as counterfactual scenario
	Differential selection bias and attrition risk to cause bias and dilution of impact	No other plausible explanations for observed outcomes or any likely confounder effects can be adjusted for
Can adapt to use existing data collected for other purposes (DHS, MICS)	Data might not be as specific as required	All-cause under-five mortality is a sensitive, specific, and time-sensitive proxy for changes in malaria-specific mortality in highly endemic countries