Cronbach's Alpha Reliability Analysis

Cronbach's alpha is a reliability coefficient that estimates the internal consistency of a multi-item scale from the number of items and the ratio of the summed item variances to the variance of the total score (equivalently, the average inter-item covariance relative to the average item variance).

크론바흐 알파는 문항 수와, 문항 분산의 합 대비 총점 분산의 비율(즉 평균 문항 분산에 대한 평균 문항 간 공분산의 상대적 크기)을 이용하여 다문항 척도의 내적일관성을 추정하는 신뢰도 계수이다.

How do I check the reliability of a questionnaire scale?

설문 척도의 신뢰도를 어떻게 확인하나요?

Cronbach's alpha estimates internal consistency reliability of a multi-item scale, with values of .70 or higher commonly treated as acceptable. It fits unidimensional scales of similarly scored items, and McDonald's omega is preferred when item loadings differ.

When to use Cronbach's Alpha Reliability Analysis

• A set of Likert-type or continuous items intended to measure one construct
• Reporting scale reliability in a survey or psychometric study
• Checking whether dropping an item would raise reliability

When to use something else

• Items load unequally on the factor; use McDonald's omega
• Multidimensional scales; compute reliability per subscale or use confirmatory factor analysis

Assumptions and requirements

• Unidimensional scale
• Tau-equivalent items (equal loadings)
• Uncorrelated errors
• Reverse-worded items recoded

What the analysis reports

• Cronbach's alpha
• Alpha if item deleted
• Corrected item-total correlations
• Inter-item correlation matrix

How to report it

The [scale name] showed good internal consistency, Cronbach's α = [value].

Related methods

• McDonald's Omega
• Confirmatory Factor Analysis
• Split-Half Reliability

Run Cronbach's Alpha Reliability Analysis on Quorant