Cronbach’s alpha is a convenient test used to estimate the reliability, or internal consistency, of a composite score. Now, what on Earth does that mean? Let’s start with reliability. Say an individual takes a Happiness Survey. Your happiness score would be highly reliable (consistent) if it produces the same or similar results when the same individual re-takes your survey, under the same conditions. However, say an individual, who, at the same level of real happiness, takes this Happiness Survey twice back-to-back, and one score shows high happiness and the other score shows low happiness—that measure would not be reliable at all.
Cronbach’s alpha gives us a simple way to measure whether or not a score is reliable. It is used under the assumption that you have multiple items measuring the same underlying construct: so, for the Happiness Survey, you might have five questions all asking different things, but when combined, could be said to measure overall happiness.
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Theoretically, Cronbach’s alpha results should give you a number from 0 to 1, but you can get negative numbers as well. A negative number indicates that something is wrong with your data—perhaps you forgot to reverse score some items. The general rule of thumb is that a Cronbach’s alpha of .70 and above is good, .80 and above is better, and .90 and above is best.
Cronbach’s alpha does come with some limitations: scores that have a low number of items associated with them tend to have lower reliability, and sample size can also influence your results for better or worse. However, it is still a widely used measure, so if your committee is asking for proof that your instrument was internally consistent or reliable, Cronbach’s alpha is a good way to go!
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