Reliability

Reliability can be defined as the extent to which scores of a measure are free from the effect of measurement error. Measurement error is reflected in random deviations of the scores observed on a measure from respondents' true scores, which are the expected values of respondents' scores if they completed the measure an infinite number of times. Mathematically, reliability is quantified as the ratio of true score variance to observed score variance or, equivalently, the square of the correlation between true scores and observed scores. Based on these indexes, reliability can range from zero (no true score variance) to one (no measurement error).

Reliability is important for both practical and theoretical purposes. Practically, it enables estimation of the standard error of measurement, an index of accuracy of a person's test score. Theoretically, reliability contributes to theory development by allowing researchers to correct for the biasing effect of measurement error on observed correlations between measures of psychological constructs and by providing researchers with an assessment of whether their measurement process needs to be improved (e.g., if reliability is low).