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Assessing test-retest reliability involves measuring the same group of participants at two separate times and calculating the correlation between their scores. This statistical relationship is commonly visualized using a scatterplot. Since standard research designs often only test participants once, researchers might specifically design a two-phase study for a new measure to evaluate this reliability. Alternatively, data from a study designed to answer a different research question can be utilized if the measure was administered multiple times. For instance, if an instructor measures students' attitudes at the start and end of a semester to detect learning changes, the correlation between those two sets of scores can simultaneously be used to assess the measure's test-retest reliability, even if no overall attitude change occurred.

Assessing Test-Retest Reliability

Test-retest correlation is the statistical coefficient calculated between two sets of scores from a measure administered at different times. A test-retest correlation of $$+.80$$ or greater is generally considered to indicate good reliability for constructs expected to be stable. For example, the Rosenberg Self-Esteem Scale demonstrated a highly reliable test-retest correlation of $$+.95$$ when administered to students twice, a week apart.

Test-Retest Correlation

To assess test-retest reliability, a researcher administers the same measure to the same group of participants at two different times and then calculates the ____ between the two sets of scores.

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