RELIAB <correlation_matrix>,<factor_matrix>,<factor_correlation_matrix>,L computes reliabilities of measurement scales according to a measurement model, which is usually estimated by the maximum likelihood factor analysis (see: FACTA?). The <factor_correlation_matrix> is given by the ROTATE operation. If the factors are orthogonal, the matrix can be omitted. L is the (optional) first line for the results. The residual covariance and correlation matrices are saved to the matrix files RCOV.M and RCORR.M, respectively. The assumptions of the measurement model may be tested by studying these matrices. In an orthogonal factor model, the residual matrix should be diagonal. The off-diagonal elements (the covariances/correlations of the measurement errors) may reveal some interesting properties of the current model. The specification MSN=<matrix_of_means,standard_deviations_and_N's> (typically MSN=MSN.M) implies computing of Cronbach's alpha for all scales. However, Cronbach's alpha is not recommended, since Tarkkonen's measure is better in every circumstance, see Vehkalahti (2000).For typical applications, sucro /RELIAB is preferable.The measurement scales corresponding to the factors are called factor images. The weights of the scales are the (rotated) factor loadings. The reliabilities of the factor images give information on the structural validity of the factor solution. When the scales are linear combinations of the observed variables, the coefficients of weights are often given by other Survo operations, such as LINREG or /FCOEFF. They may also be set by the user, according to some theory, for example. The coefficient matrix is referred to by the specification WEIGHT. By default, the reliability of an unweighted sum of the variables is computed, since it is a classical measurement scale is psychometrics. The reliabilities of second order scales can be computed by using the specification WEIGHT2. Then the coefficient matrix is formed automatically by first removing the Constant-rows of the weight-matrices and then multiplying WEIGHT and WEIGHT2. In this case, the resulting second order scale coefficients are saved in the matrix file WEIGHT2.M . M = More information on reliability of measurement scales

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