# Applied Statistics Lesson of the Day – The Matched Pairs Experimental Design

February 20, 2014 1 Comment

The **matched pairs design** is a special type of the randomized blocked design in experimental design. It has only 2 treatment levels (i.e. there is 1 factor, and this factor is binary), and a blocking variable divides the experimental units into pairs. Within each pair (i.e. each block), the experimental units are randomly assigned to the 2 treatment groups (e.g. by a coin flip). The experimental units are divided into pairs such that **homogeneity is maximized within each pair**.

For example, a lab safety officer wants to compare the durability of nitrile and latex gloves for chemical experiments. She wants to conduct an experiment with 30 nitrile gloves and 30 latex gloves to test her hypothesis. She does her best to draw a random sample of 30 students in her university for her experiment, and they all perform the same organic synthesis using the same procedures to see which type of gloves lasts longer.

She could use a completely randomized design so that a random sample of 30 hands get the 30 nitrile gloves, and the other 30 hands get the 30 latex gloves. However, since lab habits are unique to each person, this poses a confounding variable – durability can be affected by both the material and a student’s lab habits, and the lab safety officer only wants to study the effect of the material. Thus, a randomized block design should be used instead so that each student acts as a blocking variable – 1 hand gets a nitrile glove, and 1 hand gets a latex glove. Once the gloves have been given to the student, the type of glove is randomly assigned to each hand; some may get the nitrile glove on their left hand, and some may get it on their right hand. Since this design involves one binary factor and blocks that divide the experimental units into pairs, this is a matched pairs design.

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