If your test is not reliable you must try to increase your error group of answer choices true false

Theorized that measurement errors would decrease (ie. attenuate) the correlation between two tests, thus the validity would also be decreased.

He developed a correction for attenuation as a method of estimating the actual correlation between two tests (X and Y).

The correction for attenuation provides an estimate of the correlation between perfectly reliable measure of X and Y.

In practise, the correction almost always overestimates the actual correlation between X and Y. Also, this formula assumes that researchers can create a test with no measurement error, which is impossible.
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Rather than estimating the correlation that one would obtain using perfect reliability measures (which is impossible) this formula can be used to estimate the correlation between two tests if the reliability of either or both tests could be improved by a scientific amount (i.e. From .40 to .90).
- The effect of changing the reliability of one or both tests on the correlation between X and Y

This formula allows us to estimate the effects of both raising and lowering the reliability of X and Y on the correlation between X and Y.

Disadvantages: There are some problems with translating the theory of correcting for attenuation and the practise of it.
- Different researchers may have different definitions of error and may correct for different things.
- Different types of reliability measures are sometimes mixed making it difficult to evaluate connected correlations.