More and more policymakers are turning to hard evidence on public policy and programs to support their decisions and serve the public good. For many legislators, however, distinguishing strong evidence from weak evidence, or rigorous methods from unreliable methods, poses a challenge.
Mathematica’s new tool for policymakers, the four-part #EvidenceInsight video series, makes it easier for legislators with any level of expertise to understand the value of strong evidence. Each episode in the series gives a step-by-step explanation of cutting-edge research designs and methods such as Bayesian analysis, adaptive randomization, rapid cycle evaluation, and predictive analytics. These techniques are more efficient and less expensive than traditional research methods but are just as reliable.
You can also watch each #EvidenceInsight video in full:
- Episode 1: Bayesian methods can help researchers overcome the limitations of traditional evaluation techniques by using the findings from other evaluations to strengthen their evaluation results.
- Episode 2: Adaptive randomization is an alternative to traditional randomized controlled trials that allows researchers to adjust their methods in response to accumulating evidence without losing the advantages of randomization.
- Episode 3: Rapid cycle evaluation helps researchers to quickly determine the impact of small changes on program efficiency and effectiveness.
- Episode 4: Predictive analytics makes it possible to predict outcomes efficiently.
To learn more about how Mathematica’s #EvidenceInsight series and other research tools can accelerate decision making, see our Facebook, Twitter, and Instagram accounts.