Higher order and bifactor models: Issues in model identification, equivalence, and interpretation by David Flora
- Researchers often hypothesize that the covariance structure for a set of psychological variables is organized according to a set of specific, narrow constructs along with general, more broad constructs. Such a hypothesis is typically examined using either a hierarchical factor model (of which the bifactor model is a special case) or higher order factor model. This talk will explain how these two types of models are distinct conceptually, though they do have a formal mathematical relationship. Issues of model identification, equivalence, and interpretation that are not well-recognized by researchers will be emphasized. Contact: 785-864-3353, firstname.lastname@example.org Department: Center for Research Methods and Data Analysis Ticket Cost: Free Friday February 15, 2013 3:00pm - 5:00pm Joseph R. Pearson Hall, 201
University of Kansas
- University & Alumni
- Friday, February 15 @ 3:00 pm
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