Estimation of congeneric scale reliability using covariance structure analysis with nonlinear constraints.
A method of composite reliability estimation using covariance structure analysis with nonlinear constraints is outlined. To motivate the developments, initially a short overview of research is presented, demonstrating that in many cases the widely used coefficient alpha is an unsatisfactory index of scale reliability already at the population level. As an alternative, the proposed covariance structure analysis procedure is based on the theoretical formula of the scale reliability coefficient in terms of parameters pertaining to a given set of congeneric components. The described approach is illustrated with several numerical examples and its performance compared with that of coefficient alpha.
Raykov
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Department of Psychology, Fordham University, Bronx, NY 10458, USA.
D000704:Analysis of Variance; D015982:Bias; D006801:Humans; D017711:Nonlinear Dynamics; D011581:Psychological Tests / Q000706:statistics & numerical data*; D011594:Psychometrics; D015203:Reproducibility of Results