Chapman & Hall/CRC statistics in the social and behavioral sciences series
GENERAL NOTES
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"A Chapman & Hall book."
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
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Includes bibliographical references and index.
CONTENTS NOTE
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Introduction -- Mathematical foundations for structural equations modeling -- Causation -- Graph theory for causal modeling -- Structural equation models -- Identification -- Estimation of parameters -- Designing SEM studies -- Confirmatory factor analysis -- Equivalent models -- Instrumental variables -- Multilevel models -- Longitudinal models -- Nonrecursive models -- Model evaluation -- Polychoric correlation and polyserial correlation.
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SUMMARY OR ABSTRACT
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"By emphasizing causation as a functional relation between variables describing objects, with a variable a synthesis of a set of mutually exclusive attributes, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM), focusing on the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to probabilistic causation, the book reviews historical treatments of causation and recent developments in experimental psychology on studies of the perception of causation. It stresses hypothesis testing to acquire objective knowledge."--BOOK JACKET.