Structural Equation Modeling Multiple by Eid Michael (24 results)

hardcover. Condition: Very Good. Cover and edges may have some wear.

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Hardcover. Condition: new. Hardcover. The use of multiple raters can improve the validity of conclusions made on self- (and other) reports of emotions, attitudes, goals, and self-perceptions of personality. Yet analyzing these ratings requires special psychometric models that take into account the specific nature of these data. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Models for different combinations of rater types and for cross-sectional as well as longitudinal research designs are described step by step, with a strong emphasis on the substantive meaning of the latent variables in the models. User-friendly features include equation boxes, application boxes, and a companion website with Mplus and lavaan code for the books examples. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condition: New. 1st edition NO-PA16APR2015-KAP.

hardcover. Condition: New.

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Condition: New. 2024. 1st Edition. hardcover. . . . . .

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Hardcover. Condition: Brand New. 352 pages. 10.00x7.00x10.00 inches. In Stock.

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Hardback. Condition: New. The use of multiple raters can improve the validity of conclusions made on self- (and other) reports of emotions, attitudes, goals, and self-perceptions of personality. Yet analyzing these ratings requires special psychometric models that take into account the specific nature of these data. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Models for different combinations of rater types and for cross-sectional as well as longitudinal research designs are described step by step, with a strong emphasis on the substantive meaning of the latent variables in the models. User-friendly features include equation boxes, application boxes, and a companion website with Mplus and lavaan code for the book's examples.

Condition: New. 2024. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

Hardcover. Condition: new. Hardcover. The use of multiple raters can improve the validity of conclusions made on self- (and other) reports of emotions, attitudes, goals, and self-perceptions of personality. Yet analyzing these ratings requires special psychometric models that take into account the specific nature of these data. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Models for different combinations of rater types and for cross-sectional as well as longitudinal research designs are described step by step, with a strong emphasis on the substantive meaning of the latent variables in the models. User-friendly features include equation boxes, application boxes, and a companion website with Mplus and lavaan code for the books examples. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Hardcover. Condition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

Condition: New. Michael Eid, PhD, is Professor of Methods and Evaluation at the Free University of Berlin in Germany. His research focuses on measurement theory, in particular on the development of psychometric models for longitudinal and multimethod research. Since the.

Hardcover. Condition: new. Hardcover. The use of multiple raters can improve the validity of conclusions made on self- (and other) reports of emotions, attitudes, goals, and self-perceptions of personality. Yet analyzing these ratings requires special psychometric models that take into account the specific nature of these data. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Models for different combinations of rater types and for cross-sectional as well as longitudinal research designs are described step by step, with a strong emphasis on the substantive meaning of the latent variables in the models. User-friendly features include equation boxes, application boxes, and a companion website with Mplus and lavaan code for the books examples. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condition: Neu. Neuware - From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models.

Buch. Condition: Neu. Structural Equation Modeling of Multiple Rater Data | Michael Eid (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2024 | Guilford Publications | EAN 9781462555710 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Hardback. Condition: New. The use of multiple raters can improve the validity of conclusions made on self- (and other) reports of emotions, attitudes, goals, and self-perceptions of personality. Yet analyzing these ratings requires special psychometric models that take into account the specific nature of these data. From leading authorities, this book offers the first comprehensive introduction to structural equation modeling (SEM) of multiple rater data. Rather than taking a one-size-fits-all approach, the book shows how the choice of a model should be guided by measurement design and purpose. Practical recommendations are provided for selecting suitable measurement designs, raters, and psychometric models. Models for different combinations of rater types and for cross-sectional as well as longitudinal research designs are described step by step, with a strong emphasis on the substantive meaning of the latent variables in the models. User-friendly features include equation boxes, application boxes, and a companion website with Mplus and lavaan code for the book's examples.