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Randomized Block Design

Author: Sophia
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what's covered
This tutorial is going to teach you about a randomized block design, which is a little bit different than other types of designs that we've studied so far. Specifically, this lesson will cover:

Table of Contents

1. Randomized Block Design

Randomized block design is a type of experiment where participants are first divided into homogenous groups. This means that they are the same across some variable of interest, such as age, race, income, location, job, or gender.

Once participants are in their similar group, they are randomly assigned to treatment or control within that group.

An advantage is that it controls for variables that would otherwise be confounding. If we think that a subject's job has an effect, we can make sure that a proportional number of people who have the same job are assigned to a treatment and control group.

A disadvantage is that it can reduce the sample size of each group.

IN CONTEXT

Suppose you are a researcher, and you want to identify whether a new acid reflux drug is more effective than the one that's currently available. You gather 500 volunteers with acid reflux, put the number 1 on 250 cards, and the number 2 on another 250, and place all the cards in a hat. You mix them up and have people pull out numbers.

People who received a “1” receive a new drug, and those who selected “2” receive the old drug. The image below would be your original plan, starting with all these volunteers, men and women, and then you randomly assign them to groups.

The problem is, what if men and women respond differently to the drug?

A large cluster of human icons, including both male- and female-shaped figures, represents the starting population. Two arrows branch to the right, one upward and one downward, dividing the population into two separate groups. The upper group consists of purple human icons, and the lower group consists of green human icons, representing two different groups formed from the original population.

The better design is using a randomized block design, so you try something different. First, take your large group and break it into smaller subgroups of just men and just women.

A flow diagram illustrating the process of dividing a population into two separate groups, based on gender. On the left side, there is a large, diverse cluster representing the original population. This group contains icons representing people, with two different shapes used to distinguish gender: one shape has a straight-sided torso, representing a man, and the other has a flared, triangular torso, representing a woman. Two arrows originate from this central population, splitting the group in two directions. The upward arrow points to a group of men. The downward arrow points to a group of women.

The image above has nine men and 14 women; you had a lot more in the old design, but now you’re going to run the experiments essentially in parallel: one experiment for men and one experiment for women. Now you’re going to take the men and randomly assign half of them to the treatment and half to the control. Next, you’re going to take the women and assign half of them to the treatment and half to the control, which looks like this:

A flow diagram illustrating the process of dividing a population into two separate groups, based on gender.

Men and women receiving the treatment are in purple, and the men and women receiving the control are in green. You might notice there are five men receiving treatment and only four receiving control. It’s not necessary to have exactly equally sized groups.

term to know
Randomized Block Design
An experimental design where the subjects are separated into homogeneous groups, called blocks, based on some variable we think may affect the outcome of the experiment. We then run the experiment separately within each block.

2. Block Design vs. Randomized Design

By doing a block design rather than a completely randomized design, you can observe differences within the group that you might have missed had you done it with a large group.

EXAMPLE

Suppose the drug was more effective for women than for men. You would see that in this experiment here. You would see that the drug was effective for women. You would also see that it wasn't effective for men.

One minor disadvantage to running a block design is that you do lose some of the replication that you would have if you had run it in a large group. Sometimes you need to make your sample size a little bit bigger to overcome that. It might be a little bit harder to draw legitimate conclusions with small groups.

summary
In a randomized design, you saw how an experiment might miss an extra level of depth, such as men and women reacting differently to a drug. The subjects or experimental units are grouped by some similar characteristic that you think might affect the outcome. In this example, we used gender. When evaluating block design vs. randomized design, you saw that with a randomized block design, experiments run in parallel, resulting in two or more separate experiments. Then, you can compare the treatments within each of those groups.

Good luck!

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Terms to Know
Randomized Block Design

An experimental design where the subjects are separated into homogenous groups, called blocks, based on some variable we think may affect the outcome of the experiment. We then run the experiment separately within each block.

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