Curran-Bauer Analytics is pleased to announce that Dan has been honored with another teaching award in recognition of his exceptional teaching and mentoring skills. Dan was selected to receive the 2018 Jacob Cohen Award for Distinguished Teaching and Mentoring by the American Psychological Association, Division 5 (Quantitative and Qualitative Methods). He will be recognized at this year’s annual convention in San Francisco. This adds to several prior teaching awards granted to both Dan and Patrick. Dan also received the 2016 Distinguished Teaching Award for Post-Baccalaureate Instruction by the University of North Carolina at Chapel Hill, and Patrick received both the 2016 Cohen Teaching Award from the APA and the 2012 Chapman Family Teaching Award from the University of North Carolina in recognition of excellence in undergraduate teaching. Dan and Patrick bring the same level of passion and commitment to teaching in their summer workshops, disseminating quantitative methods to a broad audience of researchers in the psychological, social, and health sciences.
An equivalent model can be thought of as a re-parameterization of the original model. In other words, it is just a different way of “packaging” the same information in the data and no equivalent model can be distinguished from another based on fit alone. If you were to fit a series of equivalent models to the same sample data you obtain exactly the same chi-square test statistic, RMSEA, CFI, TLI, and any other omnibus measure of fit. It is often best to treat this as a limitation of any given study and to potentially present one or a small number of equivalent model options to the reader so that these too might be considered as plausible representations of the data.