Risky business: factor analysis of survey data – assessing the probability of incorrect dimensionalisation

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Risky business: factor analysis of survey data – assessing the probability of incorrect dimensionalisation

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a...

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Bibliographic Details
Main Authors:	van der Eijk, Cees, Rose, Jonathan
Format:	Article
Published:	Public Library of Science 2015
Subjects:	factor analysis surveys Likert systems eigenvalues principal component analysis survey data ordered categorical data applied statistics latent variables factor retention criteria
Online Access:	https://eprints.nottingham.ac.uk/28820/

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