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The word validity is primarily a measurement term, having to do with the relevance of a measuring instrument for a particular purpose, but it has been broadened to apply to an entire study. A research investigation is said to have internal validity if there are valid causal implications and is said to have external validity if the results are generalizable.

As far as measurement is concerned, the most important property of a measuring instrument is the extent to which it has been validated with respect to some gold standard whose validity has been assumed to be taken for granted. For example, if scores on a test of mathematical aptitude (the instrument to be validated) correlate highly with scores on a subsequent test of mathematical achievement (the gold standard), all is well, and the aptitude test would be regarded as valid.

In the early 20th century, the methodological literature referred to three kinds of validity: (1) content validity (expert judgment, i.e. postulation of the gold standard itself), (2) criterion-related validity (the type of validity mentioned in the previous paragraph), and (3) construct validity (the extent to which the scores obtained using a particular measuring instrument agreed with theoretical expectations). There were also subtypes of criterion-related validity {concurrent and predictive) and construct validity {convergent and discriminant), but more recently the general label "construct validity" not only has become more popular but also has been alleged to include content validity and criterion-related validity as well.

Connection Between Reliability And Validity

Reliability is concerned with the consistency of results whether or not those results are valid. It is easy to imagine a situation in which ratings given to various contestants (in a figure skating event, for example) are consistent (reliable) from one judge to another, but that all the ratings are wrong due to the personal biases of the judges.

There is a way to investigate the validity of an instrument with respect to its reliability. Suppose that a survey researcher were interested in pursuing further the relationship between performance on an aptitude test (the predictor) and performance on an achievement test (the criterion with respect to which the predictor instrument is to be validated) in which a correlation between the two of .54 has been obtained. The researcher would like to estimate what the correlation would be if it were based upon true scores rather than observed scores. There is a formula called the correction for attenuation that can be used for that purpose. The obtained correlation is divided by the product of the square roots of the estimates of the respective reliability coefficients. If the reliability coefficient for the aptitude test were estimated to be .64 and the reliability coefficient for the achievement test were estimated to be .81, application of that formula would yield a value of .75, which is considerably higher than the .54. That makes sense, because the true correlation has been attenuated (i.e. reduced) by the less-than-perfect reliabilities of the two tests.

Validity Of Instrument Versus Validity Of Scores Obtained With Instrument

Just as for reliability, it is somewhat controversial whether researchers should refer to the validity of a measuring instrument or to the validity of the scores obtained with the instrument. Some authors even go so far as to insist that any investigation of the validity of a measuring instrument should address the consequences of any actions taken on the basis of such scores.

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