In Simple Words
Think of a free health clinic offering checkups to local residents. To prove that clinic attendees represent the whole town rather than just the sickest or richest residents, doctors compare the age, income, and health history of attendees against census data for the entire town.
Observed firms before the consulting trial
- 17 project firms
- Management score 2.52
- 49 contacted nonproject firms
- Management score 2.55
Observed before intervention: 17 project and 49 contacted nonproject firms, score scale 1 to 5; difference p = 0.859. Similar measured traits do not rule out unobserved selection.
See source →Research question
Randomized trials requiring voluntary participant opt-in risk selection bias if participating firms systematically differ in unobserved capabilities or motivation from non-participating industry peers.
Participants
17 participating project firms compared against 49 nonproject contact firms and 96 ground-surveyed industry comparison textile firms near Mumbai, India.
Study Design
Cross-sectional observational comparison testing pre-intervention differences in mean assets, employee counts, debt borrowings, age, and baseline management scores using t-tests.
Results
Project firms showed no statistically significant differences from nonproject firms in pre-intervention assets ($12.8M vs $13.9M, p = 0.841), employees (204 vs 221, p = 0.552), total borrowings ($4.9M vs $5.5M, p = 0.756), or baseline BVR management scores (2.52 vs 2.55, p = 0.859).
Takeaway
Compare volunteer program participants against non-participating industry populations across observable baseline metrics to test for self-selection bias and verify external validity.
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 →- Statistically significant
A label used when a result passes a chosen statistical threshold, often p < 0.05. It does not show how large or useful an effect is. A result that is not statistically significant does not prove there is no effect.
ExampleA study reports p = 0.03 against a 0.05 threshold. It passes that test, but the effect could still be too small to matter.
American Statistical Association · Statement on p-values ↗Read more about statistically significant →