The Use of Exploratory Factor Analysis and Principal Components Analysis in Communication Research

By Hee Sun Park, René M. Dailey, Daisy Lemus. 2002

298 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3a71cb2b09f680fda2d34630af479ee0a2ca496e

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In Computer Networks and Communications

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Citations in the corpus

The Role of Motivation and Media Involvement in Explaining Internet Dependency (2008, methodology): “Perse (1990a) found instrumental viewing motivation positively related to elaboration, whereas ritualistic viewing motivation positively related to engaging in distracting behaviors. In other words, cognitive involvement was linked to instrumental motives more than to ritualistic motives. Perse (199”
Ten Steps in Scale Development and Reporting: A Guide for Researchers (2018, methodology): “Furthermore, two studies found that scale development authors rarely included critical pieces of information for readers to evaluate the quality of scales (Morrison, 2009; Park et al., 2002).”
How to factor-analyze your data right: do’s, don’ts, and how-to’s. (2010, methodology): “The “orthogonal-versus- oblique” debate marks one of the most hotly debated issues among scholars (see Comrey & Lee, 1992; Fabrigar et al., 1999; Henson & Roberts, 2006; Park et al., 2002; Preacher & MacCallum, 2003).”
The Instructional Feedback Orientation Scale: Conceptualizing and Validating a New Measure for Assessing Perceptions of Instructional Feedback (2009, methodology): “Given no a priori dimensions or factor structures with which to test a hypothesized factor solution, EFA was deemed most appropriate for scale construction in Study One (cf. Park et al., 2002).”
Confirmatory Factor Analysis and Scale Validation in Communication Research (2005, methodology): “As the name implies, EFA involves using factor analysis to find patterns of inter-correlations in the data (see Park, Dailey, & Lemus, 2002 ).”
Measuring Mindfulness: First Steps Towards the Development of a Comprehensive Mindfulness Scale (2012, methodology): “In contrast to EFA methods (e.g., principal axis factoring, maximum likelihood), PCA allows keeping as much variance as possible from the measured variables, since principal components are calculated using the total variance of the measured variables (Jolliffe 2002; Park et al. 2002).”
Relational Maintenance in Cross‐Sex Friendships Characterized by Different Types of Romantic Intent: An Exploratory Study (2005, methodology): “We subjected these items to a principal components analysis with oblique rotation, which is an appropriate method for identifying an underlying factor structure while allowing for moderate correlations among factors (Park, Dailey, & Lemus, 2002 ).”