Child Care and Early Education Research Connections

Skip to main content

Exploring treatment impact heterogeneity across sites: Challenges and opportunities for early childhood researchers


The rise of multi-site, field-based trials in early childhood research coupled with advances in statistics offer an unprecedented opportunity to understand how context affects children’s wellbeing. In the current study, we chart our journey in exploring heterogeneity in the treatment effects of an existing large-scale evaluation to provide guidance for early childhood researchers interested in studying treatment impact variation. To do so, we employ data from a professional development intervention implemented in early childhood education programs across 9 U.S. cities. We generate three broad lessons on the challenges and opportunities in examining treatment impacts across sites. First, we find that using the right statistical approach – namely fixed intercepts, random coefficient (FIRC) modeling – is critical for generating accurate estimates of cross-site variation. Second, we find that measures that traditionally have been associated with average treatment effects (e.g., program dosage) can be used to predict treatment impact. Third, we acknowledge trade-offs in statistical power for detecting average treatment effects versus treatment impact variation and discuss the implications of these trade-offs for the future design of early childhood evaluations. Findings are discussed in terms of how treatment impact variation has the potential to advance early childhood research. (author abstract)

Resource Type:
Reports & Papers
United States

Related resources include summaries, versions, measures (instruments), or other resources in which the current document plays a part. Research products funded by the Office of Planning, Research, and Evaluation are related to their project records.

- You May Also Like

These resources share similarities with the current selection. They are found by comparing the topic, author, and resource type of the currently selected resource to the rest of the library’s publications.

Selection into identification in fixed effects models, with application to Head Start

Reports & Papersview

Selection into identification in fixed effects models, with application to Head Start

Reports & Papersview

Analysis of Latina/o sociodemographic and health data sets in the United States from 1960 to 2019: Findings suggest improvements to future data collection efforts

Reports & Papersview
Release: 'v1.13.0' | Built: 2022-08-08 12:44:31 EDT