Advantages & Disadvantages of Various Experimental Designs

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  • 0:05 Experimental Design
  • 0:53 Between vs. Within
  • 3:36 Single vs. Multiple Factors
  • 5:51 Lesson Summary
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

There are many different options for researchers when deciding how to run a study. In this lesson, we'll look at some of the advantages and disadvantages of some common experimental designs.

Experimental Design

Lisa and Henry are both psychologists doing research on how to treat anxiety. Lisa wants to see if a new pill is more effective at treating anxiety than the pills that doctors have been using. Henry isn't interested in introducing a new pill to the market. He thinks that adding in a lesson on deep breathing techniques will reduce the symptoms of people who are already taking traditional anti-anxiety drugs.

How should Lisa and Henry do their studies? Experimental design is the process of deciding how to implement scientific research. There are many types of experimental design, all of which have advantages and disadvantages. Let's look closer at the strengths and limitations of several different types of experimental designs.

Between vs. Within

Lisa is interested in whether a new pill works better than the old pills at treating anxiety, while Henry wants to know if adding a lesson on breathing techniques to the treatment plan will help treat anxiety. One of the first questions that Lisa and Henry will want to answer is how to divide their subjects into groups. A between-groups design involves having two or more different groups of subjects and giving each one a treatment or no treatment.

For example, Lisa might want to divide her subjects into two groups. One group would get the traditional pill used to treat anxiety while the other would get her new pill. She could then compare how anxious the two groups are to see which pill is better.

The main strength of a between-groups design is that it allows a researcher to look at the effects of a treatment in isolation. If Lisa gave both pills to all of her subjects, there's no way she could tell if the improvement was due to one of the pills or the combination of the two pills. Even if she had the subjects take one pill for one month and another pill for the next month, the first month of taking pills could influence the second month. A between-groups design allows her to isolate the effects of both pills.

But there are limitations to a between-groups design, too. The main disadvantage is the problem of making sure that the groups are equivalent. For example, what if Lisa ended up with people who are less anxious in the group taking her pill than in the group taking the other pill? Her results might be due to differences in the groups, not due to the pills.

The opposite of a between-groups design is a within-groups design, which involves having one group of subjects and comparing their responses to different treatments. Remember Henry? He might want to use a within-groups design to test if his breathing techniques help. He could measure his subjects' anxiety when they are just taking the pills, and then teach them the breathing techniques, and then measure them again. He's essentially comparing them to themselves.

Like between-groups design, a within-groups design has both strengths and limitations. One strength of a within-groups design is that there is no question about whether the groups are equivalent or not. You are comparing people to themselves, so they are equivalent. And because you only have one group, instead of two or more, a within-groups design requires fewer subjects.

The main disadvantage of a within-groups design is that, unlike a between-groups design, it is difficult to isolate treatments from each other. There's always a risk that the treatments are affecting each other. For example, does Henry see an improvement because his breathing techniques work or because the patients have been taking the anti-anxiety pills for longer? It's hard to say for sure.

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