Methods for Increasing External Validity

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  • 0:07 External Validity
  • 1:12 Aggregation
  • 2:36 Nonreactive Measures
  • 3:49 Field Research
  • 5:00 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.

External validity is a key component of research. In this lesson, we'll look at several different ways to increase external validity, including aggregation, nonreactive measures, and field research.

External Validity

Candace is a psychologist who is interested in studying if people act differently when they are alone versus when they are with other people. She asks for volunteers for her study. When they show up for the study, she tells them that she's not ready yet and asks them to wait in a room.

In the room is a bowl of candy that has a sign on it that says, 'Take only one, please.' Some of the subjects are left completely alone in the room, while others are left in the room with someone else. Secretly, Candace watches from another room to see how many candies people take. She believes that the people alone in the room will take more than one candy.

Candace's study is very specific, but like other researchers, Candace wants to generalize her findings to tell her something about life beyond her experiment. External validity is the extent to which the results of a study can be generalized to the world at large. Let's look at some ways that researchers can increase the external validity of their studies so that they can generalize their findings.


Candace, like many psychologists, works and does research at a university. The only volunteers she can get to participate in her study are college students. But is their behavior the same as the behavior of middle-aged people? What about elementary school children? Or people who do not have the resources to go to college?

One threat to the external validity of Candace's study is the fact that her sample (or group of participants) might not represent the entire population. So what should she do? Should she just throw out the results of her study?

That would be a bit drastic. After all, she went to a lot of trouble to set up and run her study. But there is one thing she can do to help with her external validity: She can aggregate, or combine, data from other groups. For example, imagine that Candace's friend Joe ran a similar study. But Joe's participants were middle-aged office workers. By aggregating their data, Candace and Joe can see whether the results hold up across groups.

Likewise, aggregation can be used to combine data across settings (like a lab versus a doctor's office versus a school library) or across other elements of an experiment (like candy versus spare change versus pencils).

Nonreactive Measures

When Candace got the results back from her study, they confirmed her hypothesis: People who were alone took more candy than those who were with other people. The study showed that most people behave differently when they are being watched than when they are not being watched. Imagine for a moment that before Candace left a subject alone in the room, she told him that she'd be watching him from the other room. Would he take more than one piece of candy? Would he pick his nose or scratch his backside?

Because people act differently when they are being observed, the results of some studies end up not being genuine. If someone knows that they are in an experiment and being watched, they might not act the way they would in real life.

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