{"id":85453,"date":"2019-09-06T12:23:33","date_gmt":"2019-09-06T10:23:33","guid":{"rendered":"https:\/\/www.scribbr.nl\/?p=85453"},"modified":"2023-06-22T13:30:44","modified_gmt":"2023-06-22T11:30:44","slug":"types-of-validity","status":"publish","type":"post","link":"https:\/\/www.scribbr.com\/methodology\/types-of-validity\/","title":{"rendered":"The 4 Types of Validity in Research | Definitions & Examples"},"content":{"rendered":"
Validity<\/strong> 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:<\/p>\n In quantitative research<\/a>, you have to consider the reliability and validity<\/a> of your methods<\/a> and measurements.<\/p>\n 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<\/a>, which deal with the experimental design<\/a> and the generalizability<\/a> of results.<\/p>\n <\/p>\n Construct validity<\/a> evaluates whether a measurement tool really represents the thing we are interested in measuring. It\u2019s central to establishing the overall validity of a method.<\/p>\n A construct refers to a concept or characteristic that can\u2019t be directly observed, but can be measured by observing other indicators that are associated with it.<\/p>\n 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.<\/p>\n There is no objective, observable entity called \u201cdepression\u201d 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.<\/p>\n<\/div>\n Construct validity<\/a> 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\u2019s mood, self-esteem, or some other construct?<\/p>\n 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.<\/p>\n The other types of validity described below can all be considered as forms of evidence for construct validity.<\/p>\n Content validity<\/a> assesses whether a test is representative of all aspects of the construct.<\/p>\n 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 and the research is likely suffering from omitted variable bias<\/a>.<\/p>\n 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\u2019 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.<\/p>\n<\/div>\n Face validity<\/a> considers how suitable the content of a test seems to be on the surface. It\u2019s similar to content validity, but face validity is a more informal and subjective assessment.<\/p>\n You create a survey to measure the regularity of people\u2019s 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.<\/p>\n<\/div>\n As face validity is a subjective measure, it\u2019s often considered the weakest form of validity. However, it can be useful in the initial stages of developing a method.<\/p>\n 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.<\/p>\n 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.<\/p>\n To evaluate criterion validity, you calculate the correlation<\/a> 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.<\/p>\n A university professor creates a new test to measure applicants\u2019 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.<\/p>\n<\/div>\n If you want to know more about statistics<\/a>, methodology<\/a>, or research bias<\/a>, make sure to check out some of our other articles with explanations and examples.<\/p>\n <\/em>Statistics<\/strong><\/p>\n <\/em> Methodology<\/strong><\/p>\n <\/em> Research bias<\/strong><\/p>\n Face validity<\/strong><\/a> and content validity<\/strong><\/a> are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity<\/strong> is subjective, and assesses content at surface level.<\/p>\n When a test has strong face validity,<\/strong> anyone would agree that the test\u2019s questions appear to measure what they are intended to measure.<\/p>\n For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity<\/strong> (i.e., it looks like a math test).<\/p>\n On the other hand, content validity<\/strong> evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.<\/p>\n A 4th grade math test would have high content validity<\/strong> if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.<\/p>\n\n <\/div>\n <\/dd>\n <\/div>\n Criterion validity<\/a> evaluates how well a test measures the outcome it was designed to measure. An outcome can be, for example, the onset of a disease.<\/p>\n Criterion validity consists of two subtypes depending on the time at which the two measures (the criterion and your test) are obtained:<\/p>\n Convergent validity<\/strong><\/a> and discriminant validity<\/a><\/strong> are both subtypes of construct validity<\/a>. Together, they help you evaluate whether a test measures the concept it was designed to measure.<\/p>\n You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.<\/p>\n\n <\/div>\n <\/dd>\n <\/div>\n The purpose of theory-testing mode is to find evidence in order to disprove, refine, or support a theory. As such, generalizability<\/a> is not the aim of theory-testing mode.<\/p>\n Due to this, the priority of researchers in theory-testing mode is to eliminate alternative causes for relationships between variables<\/a>. In other words, they prioritize internal validity<\/a> over external validity<\/a>, including ecological validity<\/a>.<\/p>\n\n <\/div>\n <\/dd>\n <\/div>\n It\u2019s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity<\/a> of tests.<\/p>\n\n
Construct validity<\/h2>\n
What is a construct?<\/h3>\n
Example<\/h6>\n
What is construct validity?<\/h3>\n
Content validity<\/h2>\n
Example<\/h6>\n
Face validity<\/h2>\n
Example<\/h6>\n
Criterion validity<\/h2>\n
What is a criterion variable?<\/h3>\n
What is criterion validity?<\/h3>\n
Example<\/h6>\n
Other interesting articles<\/h2>\n
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Frequently asked questions about types of validity<\/h2>\n
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