Causal inference methods to study nonrandomized, preexisting development interventions.

ABSTRACT: Empirical measurement of interventions to address significant global health and development problems is necessary to ensure that resources are applied appropriately. Such intervention programs are often deployed at the group or community level. The gold standard design to measure the effectiveness of community-level interventions is the community-randomized trial, but the conditions of these trials often make it difficult to assess their external validity and sustainability. The sheer number of community interventions, relative to randomized studies, speaks to a need for rigorous observational methods to measure their impact. In this article, we use the potential outcomes model for causal inference to motivate a matched cohort design to study the impact and sustainability of nonrandomized,

SUBMITTER: Arnold BF 

PROVIDER: S-EPMC3012527 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature