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Latent Curve Analysis
Abstract
As a method for representing development, latent trait theory is presented in terms of a statistical model containing individual parameters and a structure on both the first and second moments of the random variables reflecting growth. Maximum likelihood parameter estimates and associated asymptotic tests follow directly. These procedures may be viewed as an alternative to standard repeated measures ANOVA and to first-order auto-regressive methods. As formulated, the model encompasses cohort sequential designs and allow for period or practice effects. A numerical illustration using data initially collected by Nesselroade and Baltes is presented.
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Research works printed but not linked: 24
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Singer, J. D., & Willett, J. B. (2003) · doi:10.1093/acprof:oso/9780195152968.001.0001 · Cited by 10,647
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Weston, R., & Gore, P. A. (2006) · The Counseling Psychologist · doi:10.1177/0011000006286345 · Cited by 2,718
A SAS Procedure Based on Mixture Models for Estimating Developmental Trajectories
JONES, B. L., NAGIN, D. S., & ROEDER, K. (2001) · Sociological Methods & Research · doi:10.1177/0049124101029003005 · Cited by 2,370
Analyzing developmental trajectories: A semiparametric, group-based approach.
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Metadata
- Authors
- Meredith, W., & Tisak, J.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1990-03
- Volume
- 55
- Issue
- 1
- Pages
- 107-122
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2080134433
- Cited by
- 1,463
- References
- 0
- FWCI
- 6.11
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
