Psychology research · Reference
What are reliability and validity?
Reliability and validity are the two core criteria of measurement quality in psychometrics: reliability is the consistency of a measure, and validity is whether it actually measures what it claims to measure.
Definition and the difference
Reliability and validity address two different questions about a measurement. Reliability asks, "Is the measure consistent?" — does it give similar results under similar conditions. Validity asks, "Is the measure correct?" — does it capture the construct it claims to. A common analogy is a target: a reliable measure groups its shots tightly, while a valid measure groups them on the bullseye. A measure can be reliable yet invalid (tightly grouped but off-target), but a measure that is not reliable cannot be valid, because inconsistent results cannot consistently hit the mark.
Types of reliability
Reliability is assessed in several ways. Test-retest reliability checks whether the same people score similarly when measured again after an interval. Inter-rater reliability checks whether different observers or scorers agree. Internal consistency checks whether items intended to measure the same construct correlate with one another.
Internal consistency is commonly summarised by Cronbach's alpha, a coefficient introduced by Lee Cronbach in 1951 that ranges up to 1, with higher values indicating that a scale's items hang together. Each type of reliability captures a different source of measurement error.
Types of validity
Validity also comes in several forms. Content validity concerns whether a measure covers the full scope of the construct. Construct validity — often regarded as the overarching concern — asks whether the measure behaves as the theory of the construct predicts, relating to other measures as it should. Criterion validity concerns whether the measure relates to a relevant external criterion, either at the same time (concurrent) or in the future (predictive). Establishing validity is a cumulative process built from many lines of evidence rather than a single test.
Significance for research
Reliability and validity are central to psychometrics and to credible quantitative research across the social sciences. A finding is only as trustworthy as the measures it rests on: poor reliability adds noise that can obscure real effects, while poor validity means a study may be measuring something other than what it claims. Reporting the reliability statistics and validity evidence for the instruments used is therefore a basic expectation of transparent, reproducible research.
Key facts
At a glance
- Reliability: consistency of a measure
- Validity: whether a measure assesses what it claims
- Relationship: validity requires reliability, not vice versa
- Reliability types: test-retest, inter-rater, internal consistency
- Internal consistency: summarised by Cronbach's alpha (Cronbach, 1951)
- Validity types: content, construct, criterion
Common questions
FAQ
What is the difference between reliability and validity?+
Reliability is about consistency — whether a measure gives stable, repeatable results. Validity is about accuracy of meaning — whether it measures what it claims to. A measure can be reliable without being valid, but it cannot be valid unless it is also reliable.
What is Cronbach's alpha?+
Cronbach's alpha, introduced by Lee Cronbach in 1951, is a coefficient that estimates the internal consistency of a scale — how well its items measure the same underlying construct. Higher values, up to a maximum of 1, indicate greater consistency among the items.
What are the main types of validity?+
The main types are content validity (covering the full construct), construct validity (behaving as the theory predicts and relating appropriately to other measures), and criterion validity (relating to a relevant external criterion, concurrently or predictively).
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