Using Within-Site Experimental Evidence to Reduce Cross-Site Attributional Bias in Connecting Program Components to Program Impacts

This paper considers a new method, called Cross-Site Attributional Model Improved by Calibration to Within-Site Individual Randomization Findings (CAMIC), which seeks to reduce bias in analyses that researchers use to understand what about a program’s structure and implementation leads its impact to vary. The CAMIC method takes advantage of randomization of a program component in only some sites to improve estimating the effects of other program components and implementation features that are not or cannot be randomized. The paper describes the method for potential use in the Health Profession Opportunity Grants (HPOG) program evaluation.

Stephen H. Bell, Eleanor L. Harvill, Shawn R. Moulton, and Laura Peck. (2017). Using Within-Site Experimental Evidence to Reduce Cross-Site Attributional Bias in Connecting Program Components to Program Impacts, OPRE Report #2017-13. Washington, DC: Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services.

Click here to view