Using the Linear Probability Model to Estimate Impacts on Binary Outcomes in Randomized Controlled Trials

Using the Linear Probability Model to Estimate Impacts on Binary Outcomes in Randomized Controlled Trials

Evaluation Technical Assistance Update for OAH & ACYF Teenage Pregnancy Prevention Grantees, Brief 6
Published: Dec 30, 2014
Publisher: Washington, DC: U.S. Department of Health and Human Services, Administration on Children, Youth and Families, Office of Adolescent Health
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Associated Project

Teen Pregnancy Prevention: Ensuring Rigorous Program Evaluations

Time frame: 2013-2018

Prepared for:

U.S. Department of Health and Human Services, Administration for Children and Families, Family & Youth Services Bureau

Authors

In this brief we examine methodological criticisms of the Linear Probability Model (LPM) in general and conclude that these criticisms are not relevant to experimental impact analysis. We also point out that the LPM has advantages in terms of implementation and interpretation that make it an appealing option for researchers conducting experimental impact analysis. An important caveat on these conclusions is that outside of the context of impact analysis, there can be good reasons to avoid using the LPM for binary outcomes.

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