Abstract
Pay for Success (PFS) is becoming more widely used to expand and advance innovation in the use of evidence-based programs that address societal issues. Such issues affect at-risk young children and youth, current and former incarcerated individuals, homeless individuals, and families in distress, to name a few. This brief focuses on high quality early childhood programs. The most common way to develop an analytical approach to preparing for PFS feasibility has been to use historical data and an observational perspective to hypothesize on the value of a quality early childhood treatment for an identified group of families/children. To date, most PFS projects have been built on the provision of a single treatment. Data demonstrating treatment efficacy and effectiveness for a single treatment is relatively plentiful (although not necessarily plentifully quality). Program treatments tend to be studied for treatment-specific cohorts for a specific time period. Preparing the required PFS feasibility study becomes considerably more problematic from a methodological standpoint when the PFS sponsors are considering more than one treatment to be offered in succession to the same group of families (“successively” over time). An example is a pre/post-natal home visiting program immediately followed by an in-home parental support/engagement program. An analytical methodology needs to be developed to value the marginal efficacy of each of the PFS treatments based on the time period over which they are delivered. This brief demonstrates how the Difference in Differences (DiD) statistical technique can be extended to PFS programs with successive treatments.
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