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This version was published on May 1, 2008
Applied Psychological Measurement, Vol. 32, No. 3, 211-223 (2008)
DOI: 10.1177/0146621607300860

Commingled Samples: A Neglected Source of Bias in Reliability Analysis

Niels G. Waller

University of Minnesota, nwaller{at}umn.edu

Reliability is a property of test scores from individuals who have been sampled from a well-defined population. Reliability indices, such as coefficient {alpha} and related formulas for internal consistency reliability (KR-20, Hoyt's reliability), yield lower bound reliability estimates when (a) subjects have been sampled from a single population and when (b) test items are congeneric (i.e., when items are sampled from a single latent dimension). However, when samples are commingled—that is, when they are composed of scores that are drawn from multiple populations— coefficient {alpha} and related indices can be severely biased. In most cases the bias inflates {alpha}; in other cases {alpha} is attenuated. Equations are derived for elucidating this bias in two-group mixture distributions.

Key Words: coefficient alpha • reliability • measurement bias


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