Evaluating Organizational Effectiveness: A New Strategy to Leverage Multisite Randomized Trials for Valid Assessment

Determining which organizations are more effective in implementing an intervention program is essential for theoretically and empirically characterizing exemplary practice and for intervening to enhance the capacity of ineffective ones. However, sites differ in their local ecological conditions including client composition, availability of alternative programs, and broader community context. Applying the causal inference framework, this study proposes a formal mathematical definition of an organization's local relative effectiveness attributable solely to malleable organizational practice. Capitalizing on multisite randomized trials, the identification leverages observed control group outcomes that capture some of the confounding impacts of otherwise unmeasured contextual variation. We propose a two-step mixed-effects modeling procedure that adjusts for pre-existing between-site variation. Monte Carlo simulations demonstrate its superior performance compared to conventional methods. We apply the new strategy to an evaluation of Job Corps centers nationwide serving disadvantaged youths.

Authors

Institutions

Publication Details

Journal
American Journal of Evaluation
Published
2026-04-25
DOI
https://doi.org/10.1177/10982140261438465
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating Organizational Effectiveness: A New Strategy to Leverage Multisite Randomized Trials for Valid Assessment

Jose Eos Trinidad, Guanglei Hong, Peter Kress, Zhengyan Xu et al.
American Journal of Evaluation
Advanced Causal Inference Techniques
article

Evaluating Organizational Effectiveness: A New Strategy to Leverage Multisite Randomized Trials for Valid Assessment

Jose Eos Trinidad, Guanglei Hong, Peter Kress, Zhengyan Xu, Jonah Deutsch
article en

Abstract

Determining which organizations are more effective in implementing an intervention program is essential for theoretically and empirically characterizing exemplary practice and for intervening to enhance the capacity of ineffective ones. However, sites differ in their local ecological conditions including client composition, availability of alternative programs, and broader community context. Applying the causal inference framework, this study proposes a formal mathematical definition of an organization's local relative effectiveness attributable solely to malleable organizational practice. Capitalizing on multisite randomized trials, the identification leverages observed control group outcomes that capture some of the confounding impacts of otherwise unmeasured contextual variation. We propose a two-step mixed-effects modeling procedure that adjusts for pre-existing between-site variation. Monte Carlo simulations demonstrate its superior performance compared to conventional methods. We apply the new strategy to an evaluation of Job Corps centers nationwide serving disadvantaged youths.

American Journal of Evaluation
California University of Pennsylvania (US), University of Chicago (US), Mathematica Policy Research (US), University of California, Berkeley (US)
Spencer Foundation, Institute of Education Sciences
Decent work and economic growth
Openalex Percentile: Top 5%
Advanced Causal Inference Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Evaluating Organizational Effectiveness: A New Strategy to Leverage Multisite Randomized Trials for Valid Assessment — Jose Eos Trinidad, Guanglei Hong, et al. · American Journal of Evaluation (2026) | TGRS Research Map | TGRS