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Higher order and bifactor models: Issues in model identification, equivalence, and interpretation by David Flora (Colloquium)

Associate Professor, Department of Psychology, York University

Friday February 15, 2013
3:00pm - 5:00pm
Joseph R. Pearson Hall, 201
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, quant@ku.edu
Department: Center for Research Methods and Data Analysis
Ticket Cost: Free