Testing books (e.g., Brown, 1996) typically discuss test-retest reliability (where the researcher administers a measure on two occasions and calculates the correlation between the two sets of scores as a reliability estimate), equivalent forms reliability (where the researcher administers two forms of a measure and calculates the correlation between the two sets of scores as a reliability estimate), and internal consistency reliability (where the researcher estimates the reliability of a single form administered on a single occasion). Obviously the internal consistency estimates are the easiest to get because it is not necessary to administer the measure twice or to have two forms.

Internal consistency reliability estimates come in many forms, e.g., the split-half adjusted (using the Spearman-Brown prophecy formula), the Kuder-Richardson formulas 20 and 21 (aka, K-R20 and K-R21), and Cronbach alpha. The most commonly reported of these are the K-R20 and the Cronbach alpha. Either one provides a sound estimate of reliability. However, the K-R20 is applicable only when questions are scored in a binary manner (i.e., right or wrong). Cronbach alpha has the advantage of being applicable when questions are small scales in their own right like the Likert scale (i.e., 1 2 3 4 5 type) questions found on many questionnaires. Hence, Cronbach alpha is most often the reliability estimate of choice for survey research.

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