The degree to which study results can be generalized to other settings or samples

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Many scientific disciplines, especially the social sciences, face a long battle to prove that their findings represent the wider population in real world situations.

The main criteria of external validity is the process of generalization, and whether results obtained from a small sample group, often in laboratory surroundings, can be extended to make predictions about the entire population.

The reality is that if a research program has poor external validity, the results will not be taken seriously, so any research design must justify sampling and selection methods.

The degree to which study results can be generalized to other settings or samples

What is External Validity?

In 1966, Campbell and Stanley proposed the commonly accepted definition of external validity.

“External validity asks the question of generalizability: To what populations, settings, treatment variables and measurement variables can this effect be generalized?”

External validity is usually split into two distinct types, population validity and ecological validity, and they are both essential elements in judging the strength of an experimental design.

The degree to which study results can be generalized to other settings or samples

The degree to which study results can be generalized to other settings or samples

Psychology and External Validity

The Battle Lines are Drawn

External validity often causes a little friction between clinical psychologists and research psychologists.

Clinical psychologists often believe that research psychologists spend all of their time in laboratories, testing mice and humans in conditions that bear little resemblance to the outside world. They claim that the data produced has no external validity, and does not take into account the sheer complexity and individuality of the human mind.

Before we are flamed by irate research psychologists, the truth lies somewhere between the two extremes! Research psychologists find out trends and generate sweeping generalizations that predict the behavior of groups. Clinical psychologists end up picking up the pieces, and study the individuals who lie outside the predictions, hence the animosity.

In most cases, research psychology has a very high population validity, because researchers take meticulously randomly select groups and use large sample sizes, allowing meaningful statistical analysis.

However, the artificial nature of research psychology means that ecological validity is usually low.

Clinical psychologists, on the other hand, often use focused case studies, which cause minimum disruption to the subject and have strong ecological validity. However, the small sample sizes mean that the population validity is often low.

Ideally, using both approaches provides useful generalizations, over time!

Randomization in External Validity and Internal Validity

It is also important to distinguish between external and internal validity, especially with the process of randomization, which is easily misinterpreted. Random selection is an important tenet of external validity.

For example, a research design, which involves sending out survey questionnaires to students picked at random, displays more external validity than one where the questionnaires are given to friends. This is randomization to improve external validity.

Once you have a representative sample, high internal validity involves randomly assigning subjects to groups, rather than using pre-determined selection factors.

With the student example, randomly assigning the students into test groups, rather than picking pre-determined groups based upon degree type, gender, or age strengthens the internal validity.

Work Cited

Campbell, D.T., Stanley, J.C. (1966). Experimental and Quasi-Experimental Designs for Research. Skokie, Il: Rand McNally.

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.

The degree to which study results can be generalized to other settings or samples

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.

The degree to which study results can be generalized to other settings or samples

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.

Which type of validity helps generalize results to other settings?

5. External validity. External validity refers to the extent to which the results of a study can be generalized beyond the sample. Which is to say that you can apply your findings to other people and settings.

What is external validity in a research study?

External validity refers to the extent to which the results of a study are generalizable to patients in our daily practice, especially for the population that the sample is thought to represent.

What is generalizability in research?

What is Generalizability? Very simply, generalizability is a measure of how useful the results of a study are for a broader group of people or situations. If the results of a study are broadly applicable to many different types of people or situations, the study is said to have good generalizability.

What are the 3 types of external validity?

Types of External Validity.
Population validity is how well the results from the subjects in a study sample generalize to a wider group of people. ... .
Ecological validity is how well results generated from a study can be applied to other real-world settings. ... .
Temporal validity is how well results remain accurate over time..