IALSA / wave-inclusion

How does the number of waves included into the analysis affect the conclusions from a longitudinal study?
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2016-02-02 Brief update #10

Open andkov opened 8 years ago

andkov commented 8 years ago

The paper chosen last week as the fulcrum of this research track upon examination turned out to be not on target.

However two of the studies cited in it seems to be a better fit. Two studies in question are:

Hertzog, C., Lindenberger, U., Ghisletta, P., & Oertzen, T. V. (2006). On the power of multivariate latent growth curve models to detect correlated change. Psychological methods, 11(3), 244.

and the follow up two years later

Hertzog, C., von Oertzen, T., Ghisletta, P., & Lindenberger, U. (2008). Evaluating the power of latent growth curve models to detect individual differences in change. Structural Equation Modeling, 15(4), 541-563. full text

Our plans for the next week is to take a closer look at these two papers, looking for potential leads to other publications. Also, also, let's explore Rast & Hofer (2014)

Rast, P., & Hofer, S. M. (2014). Longitudinal design considerations to optimize power to detect variances and covariances among rates of change: Simulation results based on actual longitudinal studies. Psychological methods, 19(1), 133.

and the book that they cite:

von Oertzen, T., Ghisletta, P., & Lindenberger, U. (2010). Simulating statistical power in latent growth curve modeling: A strategy for evaluating age-based changes in cognitive resources. In Resource-adaptive cognitive processes (pp. 95-117). Springer Berlin Heidelberg.

ampiccinin commented 8 years ago

You should start with Rast & Hofer. A