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Cronbach's alpha (Cronbach's ), also known as tau-equivalent reliability or coefficient alpha (coefficient ), is a reliability coefficient and a measure of the internal consistency of tests and measures. [1] [2] [3] It was named after the American psychologist Lee Cronbach.
Internal consistency is usually measured with Cronbach's alpha, a statistic calculated from the pairwise correlations between items. Internal consistency ranges between negative infinity and one. Coefficient alpha will be negative whenever there is greater within-subject variability than between-subject variability. [1]
It is a special case of Cronbach's α, computed for dichotomous scores. [2] [3] It is often claimed that a high KR-20 coefficient (e.g., > 0.90) indicates a homogeneous test. However, like Cronbach's α, homogeneity (that is, unidimensionality) is actually an assumption, not a conclusion, of reliability coefficients.
Cronbach's alpha is a generalization of an earlier form of estimating internal consistency, ... This analysis consists of computation of item difficulties and item ...
For the reliability of a two-item test, the formula is more appropriate than Cronbach's alpha (used in this way, the Spearman-Brown formula is also called "standardized Cronbach's alpha", as it is the same as Cronbach's alpha computed using the average item intercorrelation and unit-item variance, rather than the average item covariance and ...
While commercial packages routinely provide estimates of Cronbach's , specialized psychometric software may be preferred for IRT or G-theory. However, general statistical packages often do not provide a complete classical analysis (Cronbach's α {\displaystyle {\alpha }} is only one of many important statistics), and in many cases, specialized ...
Internal consistency is the extent to which the items on a scale generally measure the same thing. Cronbach's alpha values (an estimate of internal consistency) median (average) values were 0.84 for the personality pattern scales, 0.83 for the clinical syndrome scales, and 0.80 for the Grossman Facet Scales. [1]
jMetrik's item analysis includes proportion, point biserial, and biserial statistics for all response options. It calculates various reliability coefficients include Cronbach's alpha, Guttman's lambda and the Feldt-Gilmer Coefficient. The DIF analysis uses nonparametric item characteristic curves and the Mantel-Haenszel procedure, reporting ...