The Current Practice of Latent Growth Curve Modeling in the Social and Behavioral Sciences: Observations and Recommendations
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| Title: | The Current Practice of Latent Growth Curve Modeling in the Social and Behavioral Sciences: Observations and Recommendations |
|---|---|
| Language: | English |
| Authors: | Matt L. Miller (ORCID |
| Source: | International Journal of Behavioral Development. 2025 49(4):389-397. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 9 |
| Publication Date: | 2025 |
| Sponsoring Agency: | National Institutes of Health (NIH) (DHHS) |
| Contract Number: | T32A039772 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Social Science Research, Behavioral Science Research, Structural Equation Models, Statistical Analysis, Longitudinal Studies, Vocabulary |
| DOI: | 10.1177/01650254241269723 |
| ISSN: | 0165-0254 1464-0651 |
| Abstract: | We examine recommendations for three key features of latent growth curve models in the structural equation modeling framework. As a basis for the discussion, we review current practice in the social and behavioral sciences literature as found in 441 reports published in the 19 months beginning in January 2019 and compare our findings to extant recommendations. We then provide suggestions for empirical researchers, reviewing the application of these very popular models, specifically focusing on comparison of alternative change models, time metric and interval features implemented, and the treatment of individually varying time intervals. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1479228 |
| Database: | ERIC |
| Abstract: | We examine recommendations for three key features of latent growth curve models in the structural equation modeling framework. As a basis for the discussion, we review current practice in the social and behavioral sciences literature as found in 441 reports published in the 19 months beginning in January 2019 and compare our findings to extant recommendations. We then provide suggestions for empirical researchers, reviewing the application of these very popular models, specifically focusing on comparison of alternative change models, time metric and interval features implemented, and the treatment of individually varying time intervals. |
|---|---|
| ISSN: | 0165-0254 1464-0651 |
| DOI: | 10.1177/01650254241269723 |
