Economic analysis of randomized controlled trial data: a framework and feedlot cattle case study
Abstract
Abstract Livestock industry stakeholders rely on research, often randomized controlled trials, to make evidence-based decisions. Economic implications of interventions are often a major deciding factor for adoption by producers. However, economic analyses in beef feedlot trials are infrequently conducted and often suffer from inconsistent methodologies. Gaps in planning, execution, and reporting of economic assessments underscore the need for guidance and standardized approaches in conducting economic evaluations on RCT data. Our objective was to compare and contrast methodologies for assessing costs and benefits associated with livestock health and production trials and to provide scientific guidance, rationale, and recommendations for future conduct of economic analyses on RCT data. Several types of economic analyses are frequently used by agricultural economists, including cash flow budgets, enterprise budgets, gross margin analyses, cost-benefit and -effectiveness analyses, and partial budgets. Partial budgeting emerges as the most pragmatic strategy for RCT data, focusing on the marginal impact of alternative interventions or management strategies, aligning well with RCT objectives. We provided an example of applying a partial budget to an RCT conducted at a commercial beef feedlot using published data. All observed data for relevant animal performance, health, and carcass variables were included, regardless of their original statistical significance. The budget was…
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Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design.
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