A design that is a common form of blocking for comparing just two treatments, where each subject in a pair may be randomly assigned to receive one of the treatments, is called what?

A design that is a common form of blocking for comparing just two treatments, where each subject in a pair may be randomly assigned to receive one of the treatments, is called what?

• A. Matched pairs
• B. Independent samples design
• C. Cross-over design
• D. Factorial design

Answer: (A)

Matched-pairs design is used when you want to compare two treatments while controlling for differences between subjects by pairing similar individuals and randomizing treatment within each pair. By making each pair as similar as possible on relevant characteristics and then assigning one member to each treatment at random, you reduce the impact of between-person variability. This increases the precision of the comparison and the power to detect a treatment effect, especially with limited sample sizes. If you didn’t pair subjects, you’d be using an independent samples design, which leaves more between-subject variability. A cross-over design requires every subject to receive both treatments in sequence, which is a different setup and isn’t the same as randomizing within pairs. A factorial design studies more than one factor or treatment simultaneously, rather than focusing on a simple two-treatment comparison.

Matched-pairs design is used when you want to compare two treatments while controlling for differences between subjects by pairing similar individuals and randomizing treatment within each pair. By making each pair as similar as possible on relevant characteristics and then assigning one member to each treatment at random, you reduce the impact of between-person variability. This increases the precision of the comparison and the power to detect a treatment effect, especially with limited sample sizes.

If you didn’t pair subjects, you’d be using an independent samples design, which leaves more between-subject variability. A cross-over design requires every subject to receive both treatments in sequence, which is a different setup and isn’t the same as randomizing within pairs. A factorial design studies more than one factor or treatment simultaneously, rather than focusing on a simple two-treatment comparison.