Probability and Statistics Index > Statistics Definitions

If you aren’t familiar with confounding, read this article first:
Confounding Variables

What is Internal Validity?

Internal validity is a way to measure if research is sound (i.e. was the research done right?). It is related to how many confounding variables you have in your experiment. If you run an experiment and avoid confounding variables, your internal validity is high; the more confounding variables you have, the lower your internal validity. In a perfect world, your experiment would have a high internal validity. This would allow you to have high confidence that the results of your experiment are caused by only one independent variable.

internal validity

Random sampling helps to increase internal validity. Image:

For example, let’s suppose you ran an experiment to see if mice lost weight when they exercised on a wheel. You used good experimental practices, like random samples, and you used control variables to account for other things that might cause weight loss (change in diet, disease, age etc.). In other words, you accounted for the confounding variables that might affect your data and your experiment has high validity.

On the other hand, if you failed to use random sampling or control variables at all, your risk of confounding is extremely high and therefore your internal validity would be very low.

Internal Validity vs. External Validity

Internal validity is a way to gauge how strong your research methods were. External validity helps to answer the question: can the research be applied to the “real world”? If your research is applicable to other situations, external validity is high. If the research cannot be replicated in other situations, external validity is low.

Things that can Affect Internal Validity

Sometimes, confounding variables may not be that obvious. The list of usual suspects for things that can have an effect on internal validity is long and includes regression to the mean, changing the instruments during the study, participants drop out of the study and failure to complete protocols. You can find a comprehensive list of these and other potential threats here on the Sonoma State University site.

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