In Simple Words
Imagine evaluating a patient's overall recovery by aggregating individual blood tests, blood pressure, and heart rate into a single health index score—testing one combined score prevents false alarms from individual daily fluctuations and gives a clear picture of overall health.
Young job seekers in Addis Ababa
- Study comparison group
- 474.4 ETB spent in seven days
- Job application workshop
- 18.18 ETB higher spending estimated
Eight-month trial estimate; not statistically significant. Spending is measured over seven days in Ethiopian Birr. Transport arm omitted.
See source →Research question
When an intervention influences dozens of secondary indicators across varied domains (such as psychological well-being, financial behavior, and social networks), testing individual variables independently creates severe multi-testing noise and masks broad domain-level impacts.
Participants
**N = 2,841 job-seekers** evaluated across 7 secondary outcome families in Addis Ababa, Ethiopia.
Study Design
Summary index aggregation across outcome families (Job Quality, Financial Outcomes, Expectations, Mobility, Education, Wellbeing, Networks) grouped into a "super-family" tested via Benjamini et al. (2006) sharpened $q$-value procedures.
Results
Constructing standardized family indices confirmed that secondary domains (e.g., total financial expenditure $p = 0.797$, life satisfaction $p = 0.901$) showed no spurious treatment effects, maintaining statistical rigor across multi-domain evaluations.
Takeaway
Aggregate related secondary survey metrics into standardized domain indices and control False Discovery Rates across the resulting super-family of indices.