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Multiple Imputation of missing values in exploratory factor analysis of multidimensional scales: estimating latent trait scores
2016
Anales de Psicología
<p>Researchers frequently have to analyze scales in which some participants have failed to respond to some items. In this paper we focus on the exploratory factor analysis of multidimensional scales (i.e., scales that consist of a number of subscales) where each subscale is made up of a number of Likert-type items, and the aim of the analysis is to estimate participants' scores on the corresponding latent traits. Our approach uses the following steps: (1) multiple imputation creates several
doi:10.6018/analesps.32.2.215161
fatcat:q7be2tgtwjerxhqnhb4ecd3j6e