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ERIC Number: EJ1086415
Record Type: Journal
Publication Date: 2016
Pages: 23
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0022-0973
Specification Search for Identifying the Correct Mean Trajectory in Polynomial Latent Growth Models
Kim, Minjung; Kwok, Oi-Man; Yoon, Myeongsun; Willson, Victor; Lai, Mark H. C.
Journal of Experimental Education, v84 n2 p307-329 2016
This study investigated the optimal strategy for model specification search under the latent growth modeling (LGM) framework, specifically on searching for the correct polynomial mean or average growth model when there is no a priori hypothesized model in the absence of theory. In this simulation study, the effectiveness of different starting models on the search of the true mean growth model was investigated in terms of the mean and within-subject variance-covariance (V-C) structure model. The results showed that specifying the most complex (i.e., unstructured) within-subject V-C structure with the use of LRT, ?AIC, and ?BIC achieved the highest recovery rate (>85%) of the true mean trajectory. Implications of the findings and limitations are discussed.
Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A