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Stable unstable reliability theory
Author(s) -
Thomas Hoben,
Lohaus Arnold,
Domsch Holger
Publication year - 2012
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.2010.02011.x
Subject(s) - reliability (semiconductor) , mathematics , reliability engineering , econometrics , statistics , computer science , engineering , physics , thermodynamics , power (physics)
Classical reliability theory assumes that individuals have identical true scores on both testing occasions, a condition described as stable. If some individuals’ true scores are different on different testing occasions, described as unstable, the estimated reliability can be misleading. A model called stable unstable reliability theory (SURT) frames stability or instability as an empirically testable question. SURT assumes a mixed population of stable and unstable individuals in unknown proportions, with w i the probability that individual i is stable. w i becomes i ’s test score weight which is used to form a weighted correlation coefficient r w which is reliability under SURT. If all w i = 1 then r w is the classical reliability coefficient; thus classical theory is a special case of SURT. Typically r w is larger than the conventional reliability r , and confidence intervals on true scores are typically shorter than conventional intervals. r w is computed with routines in a publicly available R package.