In Simple Words
Instead of checking a sports team's fair distribution by looking at height, age, and experience in separate independent tests, you evaluate all these features together in a single system to ensure no combination of traits creates a hidden advantage for one side.
Research question
Testing experimental balance by examining one baseline variable at a time creates a multiple hypothesis testing problem, risking false positives and failing to evaluate whether baseline covariates are jointly uncorrelated with treatment assignment.
Participants
N = 31,439 randomized students in grades 4–8 and high school across 6 urban school districts.
Study Design
Zellner’s Seemingly Unrelated Regressions (SURE) model stacking multiple baseline student characteristic regressions to test the joint null hypothesis of zero correlation with assigned teacher effectiveness.
Results
SURE joint hypothesis testing yielded p-values of 0.163 across the initial randomized sample, 0.282 for the state test sample, and 0.405 for subsequent peer characteristics, statistically confirming successful experimental balance across all baseline features simultaneously.
Takeaway
Specify Zellner's SURE system estimation to execute joint hypothesis testing across all baseline covariates when validating randomization balance in multi-site RCTs.
Source and citation
See source →Read alongside the research
Plain-English glossary
Original explanations, informed by the references below. Examples are illustrations, not data from the studies above. The research text stays unchanged.
- Baseline
The starting measurements in a study. Researchers use these to compare what participants were like at the start with what happens later.
ExampleBefore a training programme starts, researchers measure workers’ earnings. That first measurement is the baseline.
GET-IT glossary · Baseline characteristics ↗Read more about baseline →