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Latent variable models: An introduction to factor, path, and structural analysis

TLDR
This text provides an introduction to a growing area in the social and behavioural sciences - the modelling of systems in which one or more variables are hypothesized but not directly observed, and provides a conceptually unified treatment of moelling.
Abstract
This text provides an introduction to a growing area in the social and behavioural sciences - the modelling of systems in which one or more variables are hypothesized but not directly observed. Providing a conceptually unified treatment of moelling of this type - exploratory and confirmatory factor analysis, path analysis and structural analysis - it is intended to introduce these techniques to individuals who have had some exposure to statistical methods in general but are beginners in this particular area. Using an inductive and informal approach, it emphasizes the use of path diagrams and a variety of concrete examples, and keeps the mathematics largely intuitive. Examples are drawn from a variety of fields, including psychometrics, sociology, psychology, education and behaviour genetics. Some introductory material is provided for LISREL, EQS and CALIS and for exploratory factor analysis programs in SAS, SPSS and BMPD, but the book is not closely tied to any one computer program or statistical package.

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Journal ArticleDOI

The aggression questionnaire.

TL;DR: Correlational analysis revealed that anger is the bridge between both physical and verbal aggression and hostility and the need to assess not only overall aggression but also its individual components.
Journal ArticleDOI

Issues and opinion on structural equation modeling

TL;DR: In the past few years, the IS field has seen a substantial increase in the number of submissions and publications using structural equation modeling techniques, which has led some to describe this approach as an example of “a second generation of multivariate analysis”.
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Principles and practice in reporting structural equation analyses.

TL;DR: Principles for reporting analyses using structural equation modeling are reviewed, and it is recommended that every report give a detailed justification of the model used, along with plausible alternatives and an account of identifiability.
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Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling.

TL;DR: Some of the questions that arise (and misconceptions that sometimes emerge) in longitudinal tests of mediational models are described and a collection of tips for structural equation modeling (SEM) of mediations are provided.
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Social capital, knowledge acquisition, and knowledge exploitation in young technology-based firms

TL;DR: The results indicate that the social interaction and network ties dimensions of social capital are indeed associated with greater knowledge acquisition, but that the relationship quality dimension is negatively associated with knowledge acquisition.