The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Analysis of Longitudinal Data: The Integration of Theoretical Model, Temporal Design, and Statistical Model
Abstract
This article argues that ideal longitudinal research is characterized by the seamless integration of three elements: (a) a well-articulated theoretical model of change observed using (b) a temporal design that affords a clear and detailed view of the process, with the resulting data analyzed by means of (c) a statistical model that is an operationalization of the theoretical model. Two general varieties of theoretical models are considered: models in which the time-related change of primary interest is continuous, and those in which it is characterized by movement between discrete states. In addition, two general types of temporal designs are considered: the longitudinal panel design and the intensive longitudinal design. For each general category of theoretical models, some of the analytic possibilities available for longitudinal panel designs and for intensive longitudinal designs are discussed. The article concludes with brief discussions of two issues particularly relevant to longitudinal research—missing data and measurement—and a few words about exploratory research.
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Citations
Cites
Regression Models and Life-Tables
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Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Analysis of Incomplete Multivariate Data
Schafer, J. L. (1997) · doi:10.1201/9781439821862 · Cited by 6,012 · cited 1×
“A much better option is to use modern missing data procedures (Schafer 1997, Schafer & Graham 2002), such as multiple imputation and maximum likelihood, which are based in statistical theory.”
Group-Based Modeling of Development
NAGIN, D. (2005) · doi:10.4159/9780674041318 · Cited by 4,164 · cited 2×
“Growth mixture models (Muthén 2001; Muthén & Muthén 2000; Muthén & Shedden 1999; Nagin 1999, 2005; Nagin & Tremblay 2001) identify subgroups corresponding to distinct patterns of growth in longitudinal data and can be used to estimate the prevalence of the patterns and to relate the patterns to…”
Validity and reliability of the Experience-Sampling Method
CSIKSZENTMIHALYI, M., & LARSON, R. (1987) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-198709000-00004 · Cited by 2,544
A comparison of inclusive and restrictive strategies in modern missing data procedures.
Collins, L. M., Schafer, J. L., & Kam, C.-M. (2001) · Psychological Methods · doi:10.1037/1082-989x.6.4.330 · Cited by 2,389
Self-citationAnalyzing developmental trajectories: A semiparametric, group-based approach.
Nagin, D. S. (1999) · Psychological Methods · doi:10.1037/1082-989x.4.2.139 · Cited by 2,346 · cited 2×
“For example, Nagin (1999) identified four prototypical trajectories of physical aggression in a sample of boys across ages 6 to 15.”
Taking Account of Time Lags in Causal Models
Gollob, H. F., & Reichardt, C. S. (1987) · Child Development · doi:10.2307/1130293 · Cited by 572
Autoregressive Latent Trajectory (ALT) Models A Synthesis of Two Traditions
Bollen, K. A., & Curran, P. J. (2004) · Sociological Methods & Research · doi:10.1177/0049124103260222 · Cited by 447
Immediate antecedents of cigarette smoking: An analysis from ecological momentary assessment.
Shiffman, S., Gwaltney, C. J., Balabanis, M. H., Liu, K. S., Paty, J. A., Kassel, J. D., Hickcox, M., & Gnys, M. (2002) · Journal of Abnormal Psychology · doi:10.1037//0021-843x.111.4.531 · Cited by 405
Cited by
Mixed-effects modeling with crossed random effects for subjects and items
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008) · Journal of Memory and Language · doi:10.1016/j.jml.2007.12.005 · Cited by 8,540
The disaggregation of within-person and between-person effects in longitudinal models of change
Curran, P. J., & Bauer, D. J. (2011) · Annual Review of Psychology · doi:10.1146/annurev.psych.093008.100356 · Cited by 2,056
Latent Variable Modeling of Differences and Changes with Longitudinal Data
McArdle, J. J. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.60.110707.163612 · Cited by 1,952
Optimal time lags in panel studies.
Dormann, C., & Griffin, M. A. (2015) · Psychological Methods · doi:10.1037/met0000041 · Cited by 856
Mediation Models for Longitudinal Data in Developmental Research
Selig, J. P., & Preacher, K. J. (2009) · Research in Human Development · doi:10.1080/15427600902911247 · Cited by 804
Metadata
- Authors
- Collins, L. M.
- Venue
- Annual Review of Psychology
- Publisher
- Annual Reviews
- Published
- 2006-01-01
- Volume
- 57
- Issue
- 1
- Pages
- 505-528
- ISSN
- 0066-4308 (ISSN-L)
- 1545-2085
- OpenAlex
- W2114704216
- Cited by
- 568
- References
- 11
- FWCI
- 2.42
- 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.
