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ERIC Number: EJ1106253
Record Type: Journal
Publication Date: 2016
Pages: 10
Abstractor: As Provided
ISSN: ISSN-0278-3193
Use of Latent Profile Analysis in Studies of Gifted Students
Mammadov, Sakhavat; Ward, Thomas J.; Cross, Jennifer Riedl; Cross, Tracy L.
Roeper Review, v38 n3 p175-184 2016
To date, in gifted education and related fields various conventional factor analytic and clustering techniques have been used extensively for investigation of the underlying structure of data. Latent profile analysis is a relatively new method in the field. In this article, we provide an introduction to latent profile analysis for gifted education researchers. We briefly trace the history of this method, focusing particularly on advancements of latent class models and their advantages over traditional clustering approaches. This is followed by the overview of statistical indicators that can be used to choose an optimal model. We illustrate use of latent profile analysis in the field through a sample study on the Big Five personality types of gifted students.
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A