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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.
Alpha is also a function of the number of items, so shorter scales will often have lower reliability estimates yet still be preferable in many situations because they are lower burden. An alternative way of thinking about internal consistency is that it is the extent to which all of the items of a test measure the same latent variable .
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 ]
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.
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 ...
Psychological statistics is application of formulas, theorems, numbers and laws to psychology.Statistical methods for psychology include development and application statistical theory and methods for modeling psychological data.
Holistic scoring is often validated by its outcomes. Consistency among rater scores, or "rater reliability," has been computed by at least eight different formulas, among them percentage of agreement, Pearson's r correlation coefficient, the Spearman-Brown formula, Cronbach's alpha, and quadratic weighted kappa.
Generalizability theory, or G theory, is a statistical framework for conceptualizing, investigating, and designing reliable observations.It is used to determine the reliability (i.e., reproducibility) of measurements under specific conditions.