When to Use Paired vs Independent Designs

Overview

Choosing between paired and independent designs affects both the confidence interval width and interpretation.

Paired Designs

• Same subjects measured twice (before/after)
• Matched pairs based on confounding variables
• Reduces variability by controlling for individual differences

Independent Designs

• Different subjects in each group
• Simpler logistics but potentially higher variability
• Required when pairing is not possible

Key Decision Factor

Use paired designs when individual-level correlation is expected to be positive, as this reduces the standard error of the difference.