In psychological and social sciences research, Cronbach's alpha is often used as a measure of internal consistency, which reflects how closely related a set of items are as a group.
The alpha coefficient ranges in value from 0 to 1 and can be used to describe the reliability of factors extracted from dichotomous (that is, questions with two possible answers) and/or multi-point formatted questionnaires or scales.
A high value of alpha (usually 0.7 or above) is taken as an indication that the items measure an underlying (or latent) construct. In other words, it indicates that the scale or test has good internal consistency and that the items within the scale reliably measure the same construct.
If the Cronbach's alpha is low (below 0.7, and especially below 0.6), it suggests that the items in the scale may not be measuring the same construct; they could be disparate and not well related. For instance, if you have a low alpha for the specific subscale, it suggests that the questions intended to measure that subscale may not be working well together to accurately and reliably assess extraversion in your sample.
However, a low alpha doesn't necessarily mean your measure is "bad." It could be that your measure is multidimensional (i.e., measuring multiple factors) rather than unidimensional. In addition, alpha is sensitive to the number of items in a scale; scales with fewer items can result in a lower alpha. Further, sometimes scales designed to cover a broad concept may naturally have a lower alpha.
ie, a low alpha can be an indicator to check your scale or test more thoroughly to understand whether all items are appropriate for your construct and your population. It may also signal the need for additional scales or tests to ensure you're capturing all aspects of a construct.
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