Evidence Library

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

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
Human Services Family Support Strengthening Families and Responsible Fatherhood

Download

Full Publication

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

John Deke

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.

Efficiency Meets Impact.
That's Progress Together.

To solve their most pressing challenges, organizations turn to Mathematica for deeply integrated expertise. We bring together subject matter and policy experts, data scientists, methodologists, and technologists who work across topics and sectors to help our partners design, improve, and scale evidence-based solutions.

Work With Us