This paper discusses the steps and decisions involved in proximal–distal economic modeling, in which social, behavioral, and academic outcomes data for children may be used to inform projections of the economic consequences of interventions. Economic projections based on proximal–distal modeling techniques may be used in cost–benefit analyses when information is unavailable for certain long-term outcomes data in adulthood or to build entire cost–benefit analyses. Although examples of proximal–distal economic analyses of preventive interventions exist in policy reports prepared for governmental agencies, such analyses have rarely been completed in conjunction with research trials. The modeling decisions on which these prediction models are based are often opaque to policymakers and other end-users. This paper aims to illuminate some of the key steps and considerations involved in constructing proximal–distal prediction models and to provide examples and suggestions that may help guide future proximal–distal analyses.
Prevention Science – Springer Journals
Published: Dec 15, 2013
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