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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

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Paperback. Zustand: New. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts - model assumptions, identification, estimation, and diagnostics - while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

paperback. Zustand: New.

Paperback. Zustand: New. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts - model assumptions, identification, estimation, and diagnostics - while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

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Zustand: New. 2026. paperback. . . . . .

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Paperback. Zustand: Brand New. 1st edition. 646 pages. 7.00x1.30x10.00 inches. In Stock.

Paperback. Zustand: new. Paperback. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts model assumptions, identification, estimation, and diagnostics while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field. This book offers a comprehensive guide to structural equation models, blending theory with practical applications. Balancing technical depth with clarity, it is an essential resource for graduate students, researchers, and practitioners in social, behavioral, health, and data sciences written by an expert who helped shape the field. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Zustand: New. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts - model assumptions, identification, estimation, and diagnostics - while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

Paperback. Zustand: new. Paperback. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts model assumptions, identification, estimation, and diagnostics while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field. This book offers a comprehensive guide to structural equation models, blending theory with practical applications. Balancing technical depth with clarity, it is an essential resource for graduate students, researchers, and practitioners in social, behavioral, health, and data sciences written by an expert who helped shape the field. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts - model assumptions, identification, estimation, and diagnostics - while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

Paperback. Zustand: New. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts - model assumptions, identification, estimation, and diagnostics - while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

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Hardback. Zustand: New. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts - model assumptions, identification, estimation, and diagnostics - while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Hardback. Zustand: New. Elements of Structural Equation Models (SEMs) blends theoretical foundations with practical applications, serving as both a learning tool and a lasting reference. Synthesizing material from diverse sources, including the author's own contributions, it provides a rigorous yet accessible guide for graduate students, faculty, and researchers across social, behavioral, health, and data sciences. The book covers essential SEM concepts - model assumptions, identification, estimation, and diagnostics - while also addressing advanced topics often overlooked, such as Bayesian SEMs, model-implied instrumental variables, and categorical variables. Readers will gain insights into missing data, longitudinal models, and comparisons with Directed Acyclic Graphs (DAGs). By presenting complex technical content in a clear, structured way, this authoritative resource deepens readers' understanding of SEMs, making it an indispensable guide for both newcomers and experts seeking a definitive treatment of the field.