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Testing Reliability Hypotheses Based on Coefficient Alpha

Authors: ALBERTO MAYDEU;

Testing Reliability Hypotheses Based on Coefficient Alpha

Abstract

We show how to test hypotheses for coefficient alpha in three different situations: (1) Hypothesis tests of whether coefficient alpha equals a prespecified value. (2) Hypothesis tests involving two statistically independent sample alphas as may arise when testing the equality of coefficient alpha across groups. (3) Hypothesis tests involving two statistically dependent sample alphas as may arise when testing the equality of alpha across time, or when testing the equality of alpha for two test scores within the same sample. We illustrate how these hypotheses may be tested in a structural equation modeling framework under the assumption of normally distributed responses and also under asymptotically distribution free (ADF) assumptions. The formulas for the hypothesis tests and computer code are given for four different applied examples.

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Keywords

Coefficient alpha, Hypothesis testing, Structural equation modeling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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