Learning power lessons: verifying the viability of impact evaluations

Learning-power-lessons-300x200Learning from one’s past mistakes is a sign of maturity. Given that metric, 3ie is growing up. We now require pilot research before funding most full impact evaluation studies. Our pilot studies requirement was developed to address a number of issues, including assessing whether there is sufficient intervention uptake, identifying or verifying whether the expected or detectable effect is reasonable and determining the similarity of participants within clusters. All of these inter-related issues have the same origin, in a problem 3ie recognized a few years ago (highlighted in this blog), which is that eager impact evaluators frequently jump into studies with incomplete information about the interventions they are evaluating. While the evaluation question may seem reasonable and justified to everyone involved, inadequate background information can cause miscalculations that render years of work and hundreds of thousands of dollars meaningless. Low intervention uptake levels, unrealistic expected or detectable effects, unexpected effect sizes or overly low intracluster correlation coefficients (ICCs) may result in insufficiently powered research and thus waste valuable evaluation resources.

Increasing the accuracy of evaluation assumptions matters. Insufficient power can torpedo an evaluation, which is the motivation behind 3ie’s proposal preparation pilot phase grants. By providing a small grant to demonstrate the viability of an evaluation, we aim to maximize the effectiveness of our limited resources to fund answerable evaluation questions. The formative research grants provide evidence of adequate intervention uptake while validating the accuracy of power calculation assumptions. We reached this point by learning from previous power assumption missteps.

Continue reading the full blog post by Benjamin DK Wood and Anna Heard. 


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