Use Sophia to knock out your gen-ed requirements quickly and affordably. Learn more
Become a Member Try for Free
×

Randomized Block Design

Author: Sophia
PDF Version

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 group of people broken into two smaller groups, one that received the pill and one that did not. The people who received the pill are purple in color and the people who did not receive the drug are green in color. Each group has a mixture of men and women.

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 group of people broken into two groups; one all male and the other all female.

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 group of people first separated into two groups; one with 9 males and the other with 14 females. The 9 males is further broken into two groups: 5 who received the treatment and 4 who did not. The 14 females are broken into two groups of 7; one group who received the treatment and the other who did not.

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!

Source: THIS TUTORIAL WAS AUTHORED BY JONATHAN OSTERS FOR SOPHIA LEARNING. PLEASE SEE OUR TERMS OF USE.

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.

© 2025 SOPHIA Learning, LLC. SOPHIA is a registered trademark of SOPHIA Learning, LLC.