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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.
[3] [4] Seemingly unaware of McDonald's work, Jöreskog first analyzed a quantity equivalent to congeneric reliability in a paper the following year. [4] [5] Jöreskog defined congeneric reliability (now labeled ρ) with coordinate-free notation, [5] and three years later, Werts gave the modern, coordinatized formula for the same. [6]
The most common internal consistency measure is Cronbach's alpha, which is usually interpreted as the mean of all possible split-half coefficients. [9] Cronbach's alpha is a generalization of an earlier form of estimating internal consistency, Kuder–Richardson Formula 20. [9]
The name of this formula stems from the fact that is the twentieth formula discussed in Kuder and Richardson's seminal paper on test reliability. [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 ...
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 ...
Split-half reliability (Spearman- Brown Prophecy) and Cronbach Alpha are popular estimates of this reliability. [5] (D) Parallel Form Reliability: It is an estimate of consistency between two different instruments of measurement. The inter-correlation between two parallel forms of a test or scale is used as an estimate of parallel form reliability.
Cronbach's alpha, [25] for example, is designed to assess the degree to which multiple tests produce correlated results. Perfect agreement is the ideal, of course, but Cronbach's alpha is high also when test results vary systematically. Consistency of coders’ judgments does not provide the needed assurances of data reliability.
The Cronbach's alpha was used to obtain reliability measures. Across one group of nine studies, alpha measures were 0.71-0.89, reflecting good internal consistency. The test adequately measures for depressive symptoms. [1] In another group of 16 studies of test-retest reliability, alpha measures were reported as 0.38–0.87. [1]