title: [Linear factor analytic models for reliability analysis of composite variables].
abstract: BACKGROUND
  Confirmatory factor analysis allows testing whether a composite variable may be considered as a reliable measure of a psychological attribute which is defined within a population.
  
  
  METHODS
  Models for parallel, tau equivalent and congeneric measurements are presented along with their reliability coefficients.
  
  
  RESULTS
  When the variables are not tau equivalent, the averaged inter-item correlation should be preferred to coefficient alpha, which is not an estimator of the reliability of the corresponding data. As a rule, interpretation of a coefficient as a reliability coefficient requires that the corresponding structural model of the composite be known. Beyond unidimensionality, simultaneous analysis of several congeneric variables through the use of cross-sectional or longitudinal hierarchical models entails fragmenting the theoretical variables.
  
  
  CONCLUSIONS
  Interpreting a composite variable whose theoretical structure is corroborated by a hierarchical model may raise some difficulties because of its multidimensionality. Reliability formulae which account for this fragmentation are detailed.
authors.affiliation: Maison de la Recherche, CERPP, B10, Université de Toulouse-Le Mirail, 5, allées Antonio-Machado, 31058 Toulouse Cedex 9. vautier@univ-tlse2.fr
authors.forename: S
authors.initials: S
authors.lastname: Vautier
authors.forename: J-P
authors.initials: JP
authors.lastname: Gaudron
authors.forename: S
authors.initials: S
authors.lastname: Jmel
mesh_terms: D005163:Factor Analysis, Statistical; D015233:Models, Statistical; D015203:Reproducibility of Results