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E.g. a scale that is 5 pounds off is reliable but not valid. A test cannot be valid unless it is reliable. Validity is also dependent on the measurement measuring what it was designed to measure, and not something else instead. [6] Validity (similar to reliability) is a relative concept; validity is not an all-or-nothing idea.
Inter-rater reliability assesses the degree of agreement between two or more raters in their appraisals. For example, a person gets a stomach ache and different doctors all give the same diagnosis. For example, a person gets a stomach ache and different doctors all give the same diagnosis.
A valid measure is one that measures what it is intended to measure. Reliability is necessary, but not sufficient, for validity. Both reliability and validity can be assessed statistically. Consistency over repeated measures of the same test can be assessed with the Pearson correlation coefficient, and is often called test-retest reliability. [26]
Test validity is the extent to which a test (such as a chemical, physical, or scholastic test) accurately measures what it is supposed to measure.In the fields of psychological testing and educational testing, "validity refers to the degree to which evidence and theory support the interpretations of test scores entailed by proposed uses of tests". [1]
Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability is defined as the probability that a product, system, or service will perform its intended function adequately for a specified period of time, OR will operate in a defined environment without failure. [1]
The mean of these differences is termed bias and the reference interval (mean ± 1.96 × standard deviation) is termed limits of agreement. The limits of agreement provide insight into how much random variation may be influencing the ratings. If the raters tend to agree, the differences between the raters' observations will be near zero.
Generalizability theory, or G theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations.It is used to determine the reliability (i.e., reproducibility) of measurements under specific conditions.
[1] [2] Criterion validity is often divided into concurrent and predictive validity based on the timing of measurement for the "predictor" and outcome. [2]: page 282 Concurrent validity refers to a comparison between the measure in question and an outcome assessed at the same time.