A Latent Class Approach to Estimating Test-Score Reliability

نویسندگان

  • Klaas Sijtsma
  • L. Andries van der Ark
  • Daniël W. van der Palm
چکیده

This study presents a general framework for single-administration reliability methods, such as Cronbach’s alpha, Guttman’s lambda-2, and method MS. This general framework was used to derive a new approach to estimating test-score reliability by means of the unrestricted latent class model. This new approach is the latent class reliability coefficient (LCRC). Unlike other single-administration reliability methods, LCRC places few restrictions on the item scores. A simulation study showed that if data are multidimensional or if double monotonicity does not hold, then LCRC is less biased relative to the true reliability than Cronbach’s alpha, Guttman’s lambda-2, method MS, and the split-half reliability coefficient.

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تاریخ انتشار 2017