Key TakeawaysCriterion validity (orcriterion-related validity) examines how well a measurement tool corresponds to other established and valid measures of the same concept.It includes concurrent validity (existing criteria) and predictive validity (future outcomes).Criterion validity is important because, without it, tests would not be able to accurately measure in a way consistent with other validated instruments.
Key Takeaways
Criterion validity assesses how well a test predicts or relates to a specific outcome or criterion. It includesconcurrent validity(correlation with existing measures) andpredictive validity(predicting future outcomes).
This approach emphasizespractical applicationsand focuses on demonstrating that the test scores are useful for predicting or estimating a particular outcome.
For example, when measuring depression with a self-report inventory, a researcher can establish criterion validity if scores on the measure correlate with external indicators of depression such as clinician ratings, number of missed work days, or length of hospital stay.
Types of Criterion Validity
Predictive
Predictive validity demonstrates that a test score can predict future performance on another criterion (Cohen & Swerdik, 2005).
Good predictive validity is important when choosing measures for employment or educational purposes, as it increases the likelihood of selecting individuals who will perform well.
The correlation between scores on standardized tests like the SAT or ACT and a student’s first-year GPA is often used as evidence for the predictive validity of these tests.
These tests aim to predict future academic performance, and a strong positive correlation between test scores and subsequent GPA would support their ability to do so.
Concurrent
This can be shown when scores on a new test correlate highly with scores on an established test measuring similar constructs (Barrett et al., 1981).
While correlational analyses are most common, researchers may also use regression.
Validation methods include comparing responses between new and established measures given to the same group, or comparing responses to expert judgments (Fink, 2010).
Note that concurrent validity does not guarantee predictive validity.
How to measure criterion validity
Identify a well-established, validated measure (criterion) that assesses the same construct as the new measure you want to validate.
This criterion measure should have demonstrated reliability and validity, serving as a benchmark for comparison.
Establishing Concurrent Validity:
Establishing Predictive Validity:
Examples of criterion-related validity
Intelligent tests
Researchers developing a new, shorter intelligence test might administer it concurrently alongside a well-established test, such as the Stanford-Binet.
If there is a high correlation between the scores from the two tests, it suggests the new test measures the same construct (intelligence), supporting its concurrent validity.
Risk assessment and dental treatment
Bader et al. (2005) studied the predictive validity of a subjective method for dentists to assess patients’ caries risk.
They analyzed data from practices that had used this method for several years to see if the risk categorization predicted the subsequent need for caries-related treatment.
Their findings showed that patients categorized as high-risk were four times more likely to receive treatment than those categorized as low-risk, while those categorized as moderate-risk were twice as likely.
This supports the predictive validity of this assessment method.
Minnesota Multiphasic Personality Inventory
The initial validation of theMMPIinvolved identifying items that differentiated between individuals with specific psychiatric diagnoses and those without, contributing to the development of scales for various psychopathologies.
This method of establishing validity, where the test is compared to an existing criterion measured at the same time, exemplifies concurrent validity.
What is the difference between criterion and construct validity?Criterion validity examines the relationship between test scores and a specific external criterion the test aims to measure or predict.This criterion is a separate, independent measure of the construct of interest.This approach emphasizespractical applicationsand focuses on demonstrating that the test scores are useful for predicting or estimating a particular outcome.Construct validityseeks to establish whether the test actually measures the underlying psychological construct it is designed to measure.It goes beyond simply predicting a criterion and aims to understand the test’stheoretical meaning.How do you increase criterion validity?There are several ways to increase criterion validity, including (Fink, 2010):– Making sure the content of the test is representative of what will be measured in the future– Using well-validated measures– Ensuring good test-taking conditions– Training raters to be consistent in their scoring
What is the difference between criterion and construct validity?Criterion validity examines the relationship between test scores and a specific external criterion the test aims to measure or predict.This criterion is a separate, independent measure of the construct of interest.This approach emphasizespractical applicationsand focuses on demonstrating that the test scores are useful for predicting or estimating a particular outcome.Construct validityseeks to establish whether the test actually measures the underlying psychological construct it is designed to measure.It goes beyond simply predicting a criterion and aims to understand the test’stheoretical meaning.
What is the difference between criterion and construct validity?
Criterion validity examines the relationship between test scores and a specific external criterion the test aims to measure or predict.This criterion is a separate, independent measure of the construct of interest.This approach emphasizespractical applicationsand focuses on demonstrating that the test scores are useful for predicting or estimating a particular outcome.Construct validityseeks to establish whether the test actually measures the underlying psychological construct it is designed to measure.It goes beyond simply predicting a criterion and aims to understand the test’stheoretical meaning.
Criterion validity examines the relationship between test scores and a specific external criterion the test aims to measure or predict.
This criterion is a separate, independent measure of the construct of interest.
Construct validityseeks to establish whether the test actually measures the underlying psychological construct it is designed to measure.
It goes beyond simply predicting a criterion and aims to understand the test’stheoretical meaning.
How do you increase criterion validity?There are several ways to increase criterion validity, including (Fink, 2010):– Making sure the content of the test is representative of what will be measured in the future– Using well-validated measures– Ensuring good test-taking conditions– Training raters to be consistent in their scoring
How do you increase criterion validity?
There are several ways to increase criterion validity, including (Fink, 2010):– Making sure the content of the test is representative of what will be measured in the future– Using well-validated measures– Ensuring good test-taking conditions– Training raters to be consistent in their scoring
There are several ways to increase criterion validity, including (Fink, 2010):
– Making sure the content of the test is representative of what will be measured in the future– Using well-validated measures– Ensuring good test-taking conditions– Training raters to be consistent in their scoring
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Saul McLeod, PhD
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
Olivia Guy-Evans, MSc
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
Charlotte NickersonResearch Assistant at Harvard UniversityUndergraduate at Harvard UniversityCharlotte Nickerson is a student at Harvard University obsessed with the intersection of mental health, productivity, and design.
Charlotte NickersonResearch Assistant at Harvard UniversityUndergraduate at Harvard University
Charlotte Nickerson
Research Assistant at Harvard University
Undergraduate at Harvard University
Charlotte Nickerson is a student at Harvard University obsessed with the intersection of mental health, productivity, and design.
