The 4 Types of Validity in Research | Definitions & Examples
In quantitative research, you have to consider the reliability and validity of your methods and measurements.
Validity tells you how accurately a method measures something. If a method measures what it claims to measure, and the results closely correspond to real-world values, then it can be considered valid. There are four main types of validity:
- Construct validity: Does the test measure the concept that it’s intended to measure?
- Content validity: Is the test fully representative of what it aims to measure?
- Face validity: Does the content of the test appear to be suitable to its aims?
- Criterion validity: Do the results accurately measure the concrete outcome they are designed to measure?
Note that this article deals with types of test validity, which determine the accuracy of the actual components of a measure. If you are doing experimental research, you also need to consider internal and external validity, which deal with the experimental design and the generalizability of results.
Table of contents
Construct validity
Construct validity evaluates whether a measurement tool really represents the thing we are interested in measuring. It’s central to establishing the overall validity of a method.
What is a construct?
A construct refers to a concept or characteristic that can’t be directly observed, but can be measured by observing other indicators that are associated with it.
Constructs can be characteristics of individuals, such as intelligence, obesity, job satisfaction, or depression; they can also be broader concepts applied to organizations or social groups, such as gender equality, corporate social responsibility, or freedom of speech.
Example
There is no objective, observable entity called “depression” that we can measure directly. But based on existing psychological research and theory, we can measure depression based on a collection of symptoms and indicators, such as low self-confidence and low energy levels.
What is construct validity?
Construct validity is about ensuring that the method of measurement matches the construct you want to measure. If you develop a questionnaire to diagnose depression, you need to know: does the questionnaire really measure the construct of depression? Or is it actually measuring the respondent’s mood, self-esteem, or some other construct?
To achieve construct validity, you have to ensure that your indicators and measurements are carefully developed based on relevant existing knowledge. The questionnaire must include only relevant questions that measure known indicators of depression.
The other types of validity described below can all be considered as forms of evidence for construct validity.
Content validity
Content validity assesses whether a test is representative of all aspects of the construct.
To produce valid results, the content of a test, survey or measurement method must cover all relevant parts of the subject it aims to measure. If some aspects are missing from the measurement (or if irrelevant aspects are included), the validity is threatened.
Example
A mathematics teacher develops an end-of-semester algebra test for her class. The test should cover every form of algebra that was taught in the class. If some types of algebra are left out, then the results may not be an accurate indication of students’ understanding of the subject. Similarly, if she includes questions that are not related to algebra, the results are no longer a valid measure of algebra knowledge.
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Face validity
Face validity considers how suitable the content of a test seems to be on the surface. It’s similar to content validity, but face validity is a more informal and subjective assessment.
Example
You create a survey to measure the regularity of people’s dietary habits. You review the survey items, which ask questions about every meal of the day and snacks eaten in between for every day of the week. On its surface, the survey seems like a good representation of what you want to test, so you consider it to have high face validity.
As face validity is a subjective measure, it’s often considered the weakest form of validity. However, it can be useful in the initial stages of developing a method.
Criterion validity
Criterion validity evaluates how well a test can predict a concrete outcome, or how well the results of your test approximate the results of another test.
What is a criterion variable?
A criterion variable is an established and effective measurement that is widely considered valid, sometimes referred to as a “gold standard” measurement. Criterion variables can be very difficult to find.
What is criterion validity?
To evaluate criterion validity, you calculate the correlation between the results of your measurement and the results of the criterion measurement. If there is a high correlation, this gives a good indication that your test is measuring what it intends to measure.
Example
A university professor creates a new test to measure applicants’ English writing ability. To assess how well the test really does measure students’ writing ability, she finds an existing test that is considered a valid measurement of English writing ability, and compares the results when the same group of students take both tests. If the outcomes are very similar, the new test has high criterion validity.
Sources in this article
We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.
This Scribbr articleMiddleton, F. (October 10, 2022). The 4 Types of Validity in Research | Definitions & Examples. Scribbr. Retrieved October 20, 2022, from https://www.scribbr.com/methodology/types-of-validity/
