[Stata] Calculating McDonald’s Omega
How it is different from Cronbach’s alpha?
📒 Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British journal of psychology, 105(3), 399-412.
McDonald’s omega and Cronbach’s alpha are both measures of internal consistency reliability, which is the extent to which items in a scale are interrelated and measure the same construct. However, there are several differences between the two coefficients.
- McDonald’s omega is based on a factor analytic approach, whereas Cronbach’s alpha is primarily based on the correlation between the questions. This means that omega is less sensitive to the number of items in a scale and the distribution of item scores. Omega also provides separate estimates of the reliability of the general factor and the group factors.
- McDonald’s omega is more robust than Cronbach’s alpha against deviations from the assumptions of tau-equivalence and uncorrelated error variances. This makes omega a more suitable measure of internal consistency in many situations.
- McDonald’s omega is less biased than Cronbach’s alpha when the number of items in a scale is small or when the items are not tau-equivalent. This means that omega is a more accurate estimate of internal consistency in these situations.
To calculate McDonald’s omega in Stata, you can use the omegacoef command created by Dr. Brian Shaw. This command estimates the scale reliability of a test using McDonald’s omega coefficient, which has many desirable statistical properties that make it preferable to the widely used Cronbach’s alpha.
Calculating McDonald’s Omega in Stata: omegacoef
Here are the steps to calculate McDonald’s omega using omegacoef command:
Step 1. Install the omegacoef command
ssc install omegacoefStep 2. Run the omegacoef command
omegacoef var1 var2 var3 The output of the omegacoef command will include the estimated McDonald’s omega coefficient.
