Since this correlation is greater than 0.80, researchers could conclude that the test has good test-retest reliability. We can use a correlation calculator to find that the Pearson Correlation Coefficient between the two sets of scores is 0.836. Suppose researchers give a test to 20 individuals and then give the same type of test one month later to the same 20 individuals. Example: Calculating Test-Retest Reliability Generally a test-retest reliability correlation of at least 0.80 or higher indicates good reliability. We could calculate the correlation of scores between the two tests to determine if the test has good test-retest reliability. 1 indicates a perfectly positive linear correlation between two scoresįor example, we may give an IQ test to 50 participants on January 1st and then give the same type of IQ test of similar difficulty to the same group of 50 participants one month later.0 indicates no linear correlation between two scores.-1 indicates a perfectly negative linear correlation between two scores.We calculate the test-retest reliability by using the Pearson Correlation Coefficient, which takes on a value between -1 and 1 where: Test-retest reliability is a specific way to measure reliability of a test and it refers to the extent that a test produces similar results over time. In other words, it’s important that the results of a test can be reproduced under the same conditions at two different points in time. When administering any type of test, it’s important that the test has reliability. Often researchers want to use some type of test to measure a construct like intelligence, aptitude, educational ability, etc.

Reliability meaning in psychology