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In psychometrics, predictive validity is the extent to which a score on a scale or test predicts scores on some criterion measure. [1] [2]For example, the validity of a cognitive test for job performance is the correlation between test scores and, for example, supervisor performance ratings.
The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.
The multitrait-multimethod (MTMM) matrix is an approach to examining construct validity developed by Campbell and Fiske (1959). [1] It organizes convergent and discriminant validity evidence for comparison of how a measure relates to other measures. The conceptual approach has influenced experimental design and measurement theory in psychology ...
[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.
The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.
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]
Precision and recall. In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all samples predicted to be positive, including those not identified correctly ...
The two measures may be for the same construct, but more often used for different, but presumably related, constructs. The two measures in the study are taken at the same time. This is in contrast to predictive validity, where one measure occurs earlier and is meant to predict some later measure. [1]