Joint Hypothesis Balance Testing in Pooled Randomization Blocks

In Simple Words

Checking whether teams in a multi-league tournament were assigned fairly by testing every player characteristic simultaneously across all divisions at once, ensuring no hidden advantages exist in any league.

Research question

In multi-site field experiments combining hundreds of separate randomization blocks, evaluating individual baseline variables sequentially fails to provide a comprehensive statistical test of overall experimental balance.

Participants

N = 31,439 randomized students (27,265 with state test scores) across 619 randomization blocks in 6 urban school districts.

Study Design

Seemingly Unrelated Regressions (SURE) joint hypothesis testing regressing assigned treatment effectiveness on a vector of baseline student characteristics (prior scores, demographics, special education, ELL status) with randomization block fixed effects.

Results

Joint hypothesis tests produced p-values of 0.163 for the full randomized sample, 0.282 for the state test sample, and 0.106 for the supplemental outcome sample, confirming that randomized assignment created statistically balanced groups.

Takeaway

Execute a SURE joint hypothesis test across all baseline covariates simultaneously to verify experimental randomization balance in blocked multi-site trials.

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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 →

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