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Science / Hygiene / Graduate / sye50

Hygiene: Evaluate Changes Without Overclaiming

Calculate a difference in differences and identify its causal assumptions.

All worksheets
5 questions0m 0s

Prerequisites

Potential outcomes, difference-in-differences designs, clustered uncertainty and research ethics.

Learn the skill

Use invented percentages of people with at least one event, counted once per period: program 30% to 20%, comparison 20% to 18%. The outcome and periods match. Difference in differences is (20 - 30) - (18 - 20) = -8 percentage points. A causal interpretation needs credible parallel untreated trends and other assumptions, not arithmetic alone.

Worked example

Both groups improved. Comparing only final values ignores their different starting points. Potential spillovers, changing composition, measurement shifts and concurrent programs can undermine the contrast. Use appropriate uncertainty estimation and participant protections.

Invented rates: program group falls from 30 to 20 percent while comparison falls from 20 to 18 percent. Difference in changes is minus 8 percentage points. A causal interpretation needs assumptions such as parallel untreated trends.
Invented rates: program group falls from 30 to 20 percent while comparison falls from 20 to 18 percent. Difference in changes is minus 8 percentage points. A causal interpretation needs assumptions such as parallel untreated trends.
Question 1 What is the program group change?
Question 2 What is the comparison group change?
Question 3 What is the difference in differences?
Question 4 What does parallel untreated trends concern?
Question 5 Which problem can threaten this design?

Further inquiry

Write the group-time contrast and its counterfactual interpretation. Specify why parallel untreated trends, stable measurement and limited interference matter. Propose sensitivity checks for changing composition and spillovers, and explain why a pretrend check cannot prove the identifying assumption. Use fictional aggregates, not student health data.

Review criteria

  • Keep percentage-point changes distinct from relative percentages.
  • Separate identification assumptions from numerical calculation and uncertainty.
  • Discuss privacy, essential access and limitations before any causal claim.