Autoregressive Latent Trajectory (ALT) Models A Synthesis of Two Traditions

By Kenneth A. Bollen, P. Curran. 2004

459 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Health, Social Psychology

View Paper: https://www.semanticscholar.org/paper/7015ba88d7d3cf117225218b04135b63eca38723

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Citations in the corpus

Twelve Frequently Asked Questions About Growth Curve Modeling (2010, background): “Two examples include the latent difference score model (McArdle, Ferrer-Caja, Hamagami, & Woodcock, 2002 ) and the autoregressive latent trajectory model (Bollen & Curran, 2004 ; Curran & Bollen, 2001 ), although several other approaches exist as well.”
The Biasing Effects of Unmodeled ARMA Time Series Processes on Latent Growth Curve Model Estimates (2005, background): “Although a few academic demonstrations of how to integrate GC models and the autoregressive (AR) model have been discussed in the literature (e.g., Bollen & Curran, 2004; Curran & Bollen, 2001; Rovine & Molenaar, 1998a), the integration of GC models with moving average (MA) and autoregressive…”
Mediation analysis. (2019, methodology): “…LGM, and LDS models, other models can be used to analyze longitudinal mediation data, including a combination of the autoregressive and LGM models (Bollen & Curran 2004) and specification of model parameters in a continuous time metric to address the problem of different time intervals of…”
Latent growth curve modeling as an integrative approach to the analysis of change (2007, methodology): “Finally, the LGCM approach has been combined with other techniques to analyze change over time such as the autoregressive model (Bollen & Curran, 2004).”
Modeling Longitudinal Data from Research on Adolescence (2009, background): “Bollen and Curran ( 2004 , 2006 ) and Curran and Bollen ( 2001 ) emphasize that panel models and latent growth curve models need not be treated as mutually exclusive choices for modeling longitudinal data.”
Multivariate longitudinal methods for studying developmental relationships between depression and academic achievement (2007, background): “…this presentation include the autoregressive cross-lag model (Jöreskog, 1970, 1974, 1979; Jöreskog & Sörbom, 1979), the autoregressive latent trajectory model (ALT; Bollen & Curran, 2004; Curran & Bollen, 2001), and the multivariate latent differential equation model (Boker, Neale, & Rausch, 2004).”
Relating Latent Change Score and Continuous Time Models (2015, background): “We also did not discuss the specification of additional growth factors (e.g., freely estimated factor loadings of the latent trait), resulting in a combination of dynamic and static models (Bollen & Curran, 2004; Oud, 2010; Voelkle, 2008).”
Developmental Changes in Working Memory, Updating, and Math Achievement. (2016, methodology): “For the math data, we fitted an autoregressive latent trajectory model (Bollen & Curran, 2004), in which the very first time-point (kindergarten) was rendered an extraneous variable and a predictor for a growth curve that described development from Grades 1 to 9.”
A Latent Growth Curve Analysis of Prosocial Behavior Among Rural Adolescents (2007, methodology): “Signifi cant 1 Autoregressive models with cross-lagged relations were also examined individually and within the context of autoregressive latent trajectory models (see Bollen & Curran, 2004; Curran & Bollen, 2001).”
On the Differences between General Cross-Lagged Panel Model and Random-Intercept Cross-Lagged Panel Model: Interpretation of Cross-Lagged Parameters and Model Choice (2020, background): “…discuss the relation between the GCLM and other longitudinal models such as the latent growth model (LGM; Meredith & Tisak, 1984, 1990) and the autoregressive latent trajectory (ALT) model (Bollen & Curran, 2004, 2006; CONTACT Satoshi Usami usami_s@p.u-tokyo.ac.jp University of Tokyo, Tokyo, Japan.”
On doing relevant and rigorous experiments: Review and recommendations (2018, background): “…refer to more extensive treatments of this topic to ensure consistency of inference in more complex situations, including where clustering is multiway or disturbances are autoregressive (e.g., Angrist & Pischke, 2008; Bollen & Curran, 2004; Cameron, Gelbach, & Miller, 2011; Cameron & Miller, 2015).”
A review of 25 years of research in bidirectionality in parent–child relationships (2016, background): “The first is the autoregressive latent trajectory model, which improves specificity regarding the level and shape of developmental change as well as the direction of influence (Bollen & Curran, 2004).”
Positivity: The Dispositional Basis of Happiness (2016, methodology): “This model allowed us to test the plausibility for the autoregressive and crosslagged structure of the state-like deviations of both constructs (Bollen and Curran 2004).”