Latent Variable Models: An Introduction to Factors, Path and Structural Analysis

Loehlin, John C.:

ISBN 10: 0898599652 / ISBN 13: 9780898599657

Edité par Lawrence Erlbaum Associates Inc, 1987

A propos de cet article

273 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 415.

N° de réf. du vendeur 2192296

Détails bibliographiques

• Titre: Latent Variable Models: An Introduction to Factors, Path and Structural Analysis
• Éditeur: Lawrence Erlbaum Associates Inc
• Date de parution: 1987
• Langue: anglais
• ISBN à 10 chiffres: 0898599652
• ISBN à 13 chiffres: 9780898599657
• Reliure: Broschiert
• État de l'article: Gut
• Catalogues du vendeur:
  • 90 Varia

A propos de ce titre

Synopsis

Book by Loehlin John C

Présentation de l'éditeur

This book is intended as an introduction to multiple-latent-variable models. Confirmatory factor analysis, path analysis, and structural equation modeling have come out of specialized niches of exploratory factor analysis and are making their bid to become basic research tools for social scientists, including sociologists; political scientists; social, educational, clinical, industrial, personality, and developmental psychologists; and marketing researchers.

The author utilizes path diagrams to explain the underlying relationships in multiple-latent-variable models. He also provides an appendix on elementary matrix algebra.

The book is not closely tied to a particular computer program or package; however, special attention is paid to two leaders in the field (LISREL and EQS). Users should have access to a latent-variable model-fitting program on the order of LISREL, EQS, CALIS, AMOS, Mx, RAMONA, or SEPATH, and an exploratory factor analysis package such as those in SPSS or SAS. In some places, a matrix manipulation facility such as that found in MINITAB, SAS, or SPSS would be useful.