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External Validity

External validity is related to generalizing. That’s the major thing you need to keep in mind. Recall that validity refers to the approximate truth of propositions, inferences, or conclusions. So, external validity refers to the approximate truth of conclusions the involve generalizations. Put in more pedestrian terms, external validity is the degree to which the conclusions in your study would hold for other persons in other places and at other times.

In science there are two major approaches to how we provide evidence for a generalization. I’ll call the first approach the Sampling Model. In the sampling model, you start by identifying the population you would like to generalize to. Then, you draw a fair sample from that population and conduct your research with the sample. Finally, because the sample is representative of the population, you can automatically generalize your results back to the population. There are several problems with this approach. First, perhaps you don’t know at the time of your study who you might ultimately like to generalize to. Second, you may not be easily able to draw a fair or representative sample. Third, it’s impossible to sample across all times that you might like to generalize to (like next year).

I’ll call the second approach to generalizing the Proximal Similarity Model. ‘Proximal’ means ‘nearby’ and ‘similarity’ means… well, it means ‘similarity’. The term proximal similarity was suggested by Donald T. Campbell as an appropriate relabeling of the term external validity (although he was the first to admit that it probably wouldn’t catch on!). Under this model, we begin by thinking about different generalizability contexts and developing a theory about which contexts are more like our study and which are less so. For instance, we might imagine several settings that have people who are more similar to the people in our study or people who are less similar. This also holds for times and places. When we place different contexts in terms of their relative similarities, we can call this implicit theoretical a gradient of similarity. Once we have developed this proximal similarity framework, we are able to generalize. How? We conclude that we can generalize the results of our study to other persons, places or times that are more like (that is, more proximally similar) to our study. Notice that here, we can never generalize with certainty – it is always a question of more or less similar.

Threats to External Validity

A threat to external validity is an explanation of how you might be wrong in making a generalization. For instance, you conclude that the results of your study (which was done in a specific place, with certain types of people, and at a specific time) can be generalized to another context (for instance, another place, with slightly different people, at a slightly later time). There are three major threats to external validity because there are three ways you could be wrong – people, places or times. Your critics could come along, for example, and argue that the results of your study are due to the unusual type of people who were in the study. Or, they could argue that it might only work because of the unusual place you did the study in (perhaps you did your educational study in a college town with lots of high-achieving educationally-oriented kids). Or, they might suggest that you did your study in a peculiar time. For instance, if you did your smoking cessation study the week after the Surgeon General issues the well-publicized results of the latest smoking and cancer studies, you might get different results than if you had done it the week before.

Improving External Validity

How can we improve external validity? One way, based on the sampling model, suggests that you do a good job of drawing a sample from a population. For instance, you should use random selection, if possible, rather than a nonrandom procedure. And, once selected, you should try to assure that the respondents participate in your study and that you keep your dropout rates low. A second approach would be to use the theory of proximal similarity more effectively. How? Perhaps you could do a better job of describing the ways your contexts and others differ, providing lots of data about the degree of similarity between various groups of people, places, and even times. You might even be able to map out the degree of proximal similarity among various contexts with a methodology like concept mapping. Perhaps the best approach to criticisms of generalizations is simply to show them that they’re wrong – do your study in a variety of places, with different people and at different times. That is, your external validity (ability to generalize) will be stronger the more you replicate your study.