While many readers may be unfamiliar with the full complexity of the covariance structure model, many may have mastered at least one of its two components - each of which is a powerful and well-known statistical technique in its own right. The first is the confirmatory factor model frequently used in psychometrics; the second, the structural equation model, is familiar to econometricians. The discussion in this volume will be particularly useful for estimating models with equality constraints and correlated errors across some but not all equations. The final chapter includes a guide to appropriate software packages.
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Scott Long is Distinguished Professor and Chancellor′s Professor of Sociology and Statistics at Indiana University, Bloomington. He teaches quantitative methods both at Indiana University and at the ICSPR Summer Program. His earlier research examined gender differences in the scientific career. In recent years, he has collaborated with Eliza Pavalko, Bernice Pescsolido, John Bancroft, Julia Heiman and others in studies of health and aging, stigma and mental health, and human sexuality.
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