"Even with our very different orientations to data collection and analysis, we both found several chapters useful for our own research interests. Generally, the discussions are widely applicable and will be useful in many fields. . . . Various chapters of the book would be excellent supplementary reading in courses dealing with structural equation modeling or categorical data analysis. . . . Space does not permit even passing comment on the other excellent chapters. . . . In the words of the editors in the preface, ′we now have a better understanding of how models with latent variables relate to other models, and how ostensibly different latent variable models relate to each other.′ While this understanding is by no means complete, collectively the chapters in this volume move us a bit closer to that goal." --Charles J. Brody and Tammy Greer in Sociological Practice With contributions from the leading national and international researchers, this book shows how latent variables can be incorporated with other data analysis strategies (such as structural equation modeling, regression analysis, log-linear modeling, and prediction analysis) and applied in developmental research (such as cohort-time of measurement-age analysis, log-linear modeling of behavior genetics hypothesis, and analyses of repeatedly observed state measures). Detailed explanations of the computations and of software packages that can be used to do these techniques are included with each statistical method. Latent Variables Analysis is appropriate for readers with an introductory statistics background. Professionals and researchers interested in research methods, evaluation, developmental psychology, and family studies will find Latent Variables Analysis to be an invaluable resource.
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Methodology and Statistics, Michigan State University.
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