External Validity in Psychology: Threats, Definition & Examples

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  • 0:02 What Is External Validity?
  • 0:50 Evidence for Generalization
  • 2:41 Threats to External Validity
  • 4:47 Lesson Summary
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Lesson Transcript
Instructor: Yolanda Williams

Yolanda has taught college Psychology and Ethics, and has a doctorate of philosophy in counselor education and supervision.

External validity is related to how well your study results are able to be generalized to other people, times, and situations. Learn more about external validity and the threats to external validity.

Definition of External Validity

External validity is the extent to which your research results apply to more than just the people in your experiment. In other words, would your research conclusions hold true for other individuals in different locations and at different times? External validity is related to the concept of generalization

There are three types of generalization:

  1. Population generalization: Can your results apply to other people in the general population beyond those that you have tested?
  2. Environmental generalization: Can your results apply to other situations or environments beyond those that you used in your experiment?
  3. Temporal generalization: Can your research findings apply at any time and not just during the specific time or season that your experiment was conducted?

Evidence for Generalization

There are two methods that can be used to improve external validity: the sampling model and the proximal similarity model.

Suppose we were researching the study habits of married college females in the United States. Our population would consist of all married females who attend college in the U.S. Since there are well over 300,000 members of this population, it would be impossible to collect data from every one. Instead we collect data from a sample, which is a subset of the population.

You want to make sure that the sample is truly reflective of the population so that you can draw accurate conclusions. After we collect and analyze the data from our sample, we use it in order to draw conclusions. If the sample is truly representative of the population, we should be able to generalize our results back to the general population (all married female college students). This is an example of the sampling model.

In cases where we are not able to obtain a representative sample, we can use the proximal similarity model. We would think about the characteristics of our study and the characteristics of the populations that we would like to generalize our results to. Then we create a gradient of similarity, on which we place different contexts in terms of how similar they are to our study.

The assumption is that we would be able to generalize the results better to the populations, times, and situations that are similar to the sample than we would to populations, times, and situations that are different. For example, if our study only consisted of African-American married college women, we would not be able to generalize our study to Chinese-American married college women because the people in the sample are not similar to the population that we want to generalize to. If our study were conducted in the 1970s, our research results would not be able to be generalized to the present time.

Threats to External Validity

There are several factors that can threaten our ability to generalize our results. They include:

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