Structural equation models and the quantification of behavior

Quantifying behavior often involves using variables that contain measurement errors and formulating multiequations to capture the relationship among a set of variables. Structural equation models (SEMs) refer to modeling techniques popular in the social and behavioral sciences that are equipped to h...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2011-09, Vol.108 (Supplement 3), p.15639-15646
Main Authors: Bollen, Kenneth A, Noble, Mark D
Format: Article
Language:English
Subjects:
Animals
behavior
Behavior - physiology
Behavioral sciences
Colloquium Papers
Economic models
equations
Estimators
Factor analysis
Humans
Instrumental variables estimation
Knowledge
Mathematical independent variables
Measurement errors
Modeling
Models, Biological
Parametric models
quantitative analysis
Sleep - physiology
Sleep Wake Disorders - physiopathology
Statistical discrepancies
Structural equation models
Trajectories
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Summary:Quantifying behavior often involves using variables that contain measurement errors and formulating multiequations to capture the relationship among a set of variables. Structural equation models (SEMs) refer to modeling techniques popular in the social and behavioral sciences that are equipped to handle multiequation models, multiple measures of concepts, and measurement error. This work provides an overview of latent variable SEMs. We present the equations for SEMs and the steps in modeling, and we provide three illustrations of SEMs. We suggest that the general nature of the model is capable of handling a variety of problems in the quantification of behavior, where the researcher has sufficient knowledge to formulate hypotheses.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1010661108