Advanced studies of individual differences linear dynamic models for longitudinal data analysis.
By Fumiaki Hamagami, J. Mcardle. 2001
87 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/df02d38bb2c08fc662732bbc10ac04b294db9ed9
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Citations in the corpus
- Relating Latent Change Score and Continuous Time Models (2015, background): “This has been demonstrated before in a series of publications (Bergstrom, 1988; Hamagami & McArdle, 2001; Oud & Jansen, 2000; see Voelkle et al., 2012, for more detailed references).”
- Multivariate longitudinal methods for studying developmental relationships between depression and academic achievement (2007, methodology): “Bivariate latent difference score growth model Latent difference score (LDS) growth models (Hamagami & McArdle, 2001; McArdle, 2001; McArdle & Hamagami, 2001) are an extension of the latent growth curve and autoregressive time-series models.”
- 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): “Notably, in the last few years the random-intercept CLPM (RI-CLPM; Hamaker et al., 2015) has rapidly become a popular approach among psychologists, reaching more than 600 citations on Google Scholar as of August 2020. A major strength of this model is that it can account for stable trait factors tha”