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Internal reliability

You know how to examine how individual items perform in your measure, but what about how well those items relate to each other - the overall internal reliability of a measure? Coefficient alpha (also called Cronbach's alpha) and split-half reliability are two common ways of assessing reliability. These statistics are a function of the measure length and items' interrelatedness, which you just investigated by looking at the correlation matrix.

In reliability values greater than 0.8 are desired, though some fields of study have higher or lower guidelines.

Do the results of alpha() and splitHalf() indicate the gcbs dataset has acceptable reliability?

This exercise is part of the course

Factor Analysis in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Estimate coefficient alpha
___(gcbs)
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