What is Reliability?
Reliability is the consistency or reproducibility of a measurement. A reliable measure produces the same results when applied repeatedly to the same subject under the same conditions.
How it works
Types of reliability include test-retest (same results over time), inter-rater (same results across different raters), internal consistency (items within a scale measure the same construct), and parallel forms (equivalent versions of a test produce equivalent scores). Reliability sets the upper limit on validity: an unreliable measure cannot be valid because it measures too much random noise. However, a reliable measure is not necessarily valid: a broken thermometer that always reads 98.6°F is perfectly reliable but not valid.
Applied example
A depression screening tool administered to the same person on Monday and Wednesday (with no treatment in between) that produces scores of 15 and 4 respectively has poor test-retest reliability. The fluctuation reflects measurement noise rather than genuine change in depression.
Why it matters
Reliability is the prerequisite for meaningful measurement: without it, observed changes cannot be distinguished from random fluctuation, making all subsequent analysis meaningless.
