Applications of the confirmatory factor analysis block-diagonal model to published data on 18 multitrait-multimethod matrices were reviewed to show widespread estimation problems. Possible causes of estimation difficulties were explored using computer simulations. These problems make the block-diagonal approach less useful than has generally been…

Selectivity problems are discussed in terms of a general model that is estimated by the maximum likelihood method. Both single-group and multiple-group analyses are considered. An extension of the general model to latent variable models is discussed. (Author/PN)

The problem of spurious significance in multivariate exploratory research is discussed. When a very large number of statistical tests are performed, many tests will be significant on the basis of chance alone. To counter this problem, the use of two sign tests to analyze sets of results has been suggested; the chance expectation [CE test] assesses…

Implications of ignoring correlated error on parameter estimates in some simple structural equation models are examined. It is shown analytically and empirically through simulation that ignoring positive between-construct correlated error overestimates the structural parameter linking the two constructs. Effects become more pronounced with…

Computer generated data are used to show that Slinde and Linn's criticism of the usefulness of the Rasch model for equating (EJ 189 585) may have been the result of an artifact produced by the manner in which the samples were chosen in their study. (CTM)

Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…

The utility of the biomedical model of adjusted statistics is demonstrated. The model is recommended for use by educational researchers to randomize subjects for a more accurate estimate of school programs' success or failure when compared across classrooms or other units. (Author/MH)