Premium
Reliability of multiple‐component measuring instruments: Improved evaluation in repeated measure designs
Author(s) -
Raykov Tenko
Publication year - 2007
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 - 10.1348/000711006x100464
Subject(s) - reliability (semiconductor) , variance components , measure (data warehouse) , variance (accounting) , statistics , component (thermodynamics) , covariance , mathematics , interval estimation , analysis of covariance , confidence interval , scale (ratio) , reliability engineering , interval (graph theory) , point estimation , repeated measures design , point (geometry) , computer science , algorithm , data mining , engineering , power (physics) , physics , geometry , accounting , quantum mechanics , combinatorics , business , thermodynamics
A covariance structure analysis method for improved point and interval estimation of composite reliability in repeated measure designs is outlined that accounts for specificity variance. The approach also permits the testing of time‐invariance in reliability of multiple‐component instruments in terms of the ratio of ‘pure’ measurement error variance to observed scale score variance. In addition, the procedure allows interval estimation of the difference in composite reliability coefficients across assessment occasions. The method described is illustrated with data from a cognitive intervention study.