Cohen’s Kappa and Cronbach’s Alpha are both reliability coefficients used in research, but they assess different types of reliability:

Here’s a table summarizing the key differences:

FeatureCohen’s KappaCronbach’s Alpha
Type of ReliabilityInter-raterInternal Consistency
Data TypeNominalOrdinal/Interval
PurposeAssess agreement between ratersAssess consistency of a test/scale
Range of Values-1 to 10 to 1

Choosing the right statistic depends on your research question:

Also, from another source:

Cohen’s kappa and Cronbach’s alpha are both statistical measures used in different contexts, primarily in the field of psychometrics, but they serve different purposes and are applied in different scenarios.

  1. Cohen’s Kappa:
    • Cohen’s kappa is a statistic used to measure inter-rater reliability for categorical items. It assesses the degree of agreement between two raters who classify items into mutually exclusive categories.
    • It is particularly useful when evaluating the agreement between two raters or observers who may assign items into different categories. This could be in fields such as psychology, medicine, or any other discipline where subjective judgments need to be made.
    • The value of kappa ranges from -1 to 1. A value of 1 indicates perfect agreement, 0 indicates agreement equivalent to chance, and negative values suggest systematic disagreement.
    • Cohen’s kappa is sensitive to the marginal distributions of the categories being rated.
  2. Cronbach’s Alpha:
    • Cronbach’s alpha, often referred to simply as alpha, is a measure of internal consistency reliability. It is commonly used in psychology and other social sciences to assess the reliability of a psychometric instrument, such as a questionnaire or test.
    • It measures how closely related a set of items are as a group. In other words, it evaluates whether the items in a scale or test are all measuring the same underlying construct.
    • Alpha values range from 0 to 1, where higher values indicate greater internal consistency. A common rule of thumb is that alpha should be at least 0.70 for a scale to be considered reliable, though this threshold can vary depending on the context.
    • Cronbach’s alpha is sensitive to the number of items in the scale and the average intercorrelation among the items. It assumes that the items are measuring a unidimensional construct.

In summary, Cohen’s kappa is used to measure agreement between raters for categorical data, while Cronbach’s alpha is used to assess the internal consistency reliability of a scale or test composed of multiple items. They serve different purposes and are applied in different contexts within the field of psychometrics.