Latent variable modeling
نویسنده
چکیده
doi: 10.3969/j.issn.1002-0829.2012.02.010 National Center for Research on Evaluation, Standards, and Student Testing, University of California, Los Angeles, CA, USA *Correspondence: [email protected] A latent variable model, as the name suggests, is a statistical model that contains latent, that is, unobserved, variables. Their roots go back to Spearman’s 1904 seminal work on factor analysis, which is arguably the first well-articulated latent variable model to be widely used in psychology, mental health research, and allied disciplines. Because of the association of factor analysis with early studies of human intelligence, the fact that key variables in a statistical model are, on occasion, unobserved has been a point of lingering contention and controversy. The reader is assured, however, that a latent variable, defined in the broadest manner, is no more mysterious than an error term in a normal theory linear regression model or a random effect in a mixed model.
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