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  1.  5
    To center or not to center? Investigating inertia with a multilevel autoregressive model.Ellen L. Hamaker & Raoul P. P. P. Grasman - 2014 - Frontiers in Psychology 5.
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  2.  13
    What's in a Day? A Guide to Decomposing the Variance in Intensive Longitudinal Data.Silvia de Haan-Rietdijk, Peter Kuppens & Ellen L. Hamaker - 2016 - Frontiers in Psychology 7.
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  3.  20
    Incorporating measurement error in n = 1 psychological autoregressive modeling.Noémi K. Schuurman, Jan H. Houtveen & Ellen L. Hamaker - 2015 - Frontiers in Psychology 6.
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  4.  3
    From Data to Causes III: Bayesian Priors for General Cross-Lagged Panel Models.Michael J. Zyphur, Ellen L. Hamaker, Louis Tay, Manuel Voelkle, Kristopher J. Preacher, Zhen Zhang, Paul D. Allison, Dean C. Pierides, Peter Koval & Edward F. Diener - 2021 - Frontiers in Psychology 12.
    This article describes some potential uses of Bayesian estimation for time-series and panel data models by incorporating information from prior probabilities in addition to observed data. Drawing on econometrics and other literatures we illustrate the use of informative “shrinkage” or “small variance” priors while extending prior work on the general cross-lagged panel model. Using a panel dataset of national income and subjective well-being we describe three key benefits of these priors. First, they shrink parameter estimates toward zero or toward each (...)
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    Discrete- vs. Continuous-Time Modeling of Unequally Spaced Experience Sampling Method Data.Silvia de Haan-Rietdijk, Manuel C. Voelkle, Loes Keijsers & Ellen L. Hamaker - 2017 - Frontiers in Psychology 8.
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