Latent Growth Curve Models.
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| Title: | Latent Growth Curve Models. |
|---|---|
| Authors: | Burant, Christopher J.1,2 cxb43@case.edu |
| Source: | International Journal of Aging & Human Development. Apr2016, Vol. 82 Issue 4, p336-350. 15p. 8 Diagrams. |
| Subject Terms: | *Mental depression, *Longitudinal method, Chi-squared test, Confidence intervals, Goodness-of-fit tests, Research funding, Structural models, Structural equation modeling, Data analysis software, Descriptive statistics |
| Geographic Terms: | Midwest (U.S.) |
| Abstract: | The latent growth curve model (LGCM) is a useful tool in analyzing longitudinal data. It is particularly suitable for gerontological research because the LGCM can track the trajectories and changes of phenomena (e.g., physical health and psychological well-being) over time. Specifically, the LGCM compares lines of change across a set of individuals and determines the overall model's line of change. LGCMs can be used to track either linear or curvilinear trajectories. Since the technique uses structural equation modeling, models are also adjusted for measurement error. This article will present a step-by-step approach to setting up, analyzing, and interpreting an LGCM using post—hospitalization recovery in depressive symptomatology as an example. This article will demonstrate how to test linear, quadratic, and freely estimated lines of change using LGCMs with the purpose of finding the line of trajectory for depressive symptoms that best fits the data. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Aging & Human Development is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 114528755 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Latent Growth Curve Models. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Burant%2C+Christopher+J%2E%22">Burant, Christopher J.</searchLink><relatesTo>1,2</relatesTo><i> cxb43@case.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Aging+%26+Human+Development%22">International Journal of Aging & Human Development</searchLink>. Apr2016, Vol. 82 Issue 4, p336-350. 15p. 8 Diagrams. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Mental+depression%22">Mental depression</searchLink><br />*<searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br /><searchLink fieldCode="DE" term="%22Chi-squared+test%22">Chi-squared test</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Goodness-of-fit+tests%22">Goodness-of-fit tests</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+models%22">Structural models</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Midwest+%28U%2ES%2E%29%22">Midwest (U.S.)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The latent growth curve model (LGCM) is a useful tool in analyzing longitudinal data. It is particularly suitable for gerontological research because the LGCM can track the trajectories and changes of phenomena (e.g., physical health and psychological well-being) over time. Specifically, the LGCM compares lines of change across a set of individuals and determines the overall model's line of change. LGCMs can be used to track either linear or curvilinear trajectories. Since the technique uses structural equation modeling, models are also adjusted for measurement error. This article will present a step-by-step approach to setting up, analyzing, and interpreting an LGCM using post—hospitalization recovery in depressive symptomatology as an example. This article will demonstrate how to test linear, quadratic, and freely estimated lines of change using LGCMs with the purpose of finding the line of trajectory for depressive symptoms that best fits the data. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Aging & Human Development is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/0091415016641692 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 336 Subjects: – SubjectFull: Mental depression Type: general – SubjectFull: Longitudinal method Type: general – SubjectFull: Chi-squared test Type: general – SubjectFull: Confidence intervals Type: general – SubjectFull: Goodness-of-fit tests Type: general – SubjectFull: Research funding Type: general – SubjectFull: Structural models Type: general – SubjectFull: Structural equation modeling Type: general – SubjectFull: Data analysis software Type: general – SubjectFull: Descriptive statistics Type: general – SubjectFull: Midwest (U.S.) Type: general Titles: – TitleFull: Latent Growth Curve Models. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Burant, Christopher J. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 00914150 Numbering: – Type: volume Value: 82 – Type: issue Value: 4 Titles: – TitleFull: International Journal of Aging & Human Development Type: main |
| ResultId | 1 |
