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Longitudinal dynamic analyses of cognition in the health and retirement study panel

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Abstract

The purpose of this paper is to highlight some classic issues in the measurement of change and to show how contemporary solutions can be used to deal with some of these issues. Five classic issues will be raised here: (1) Separating individual changes from group differences; (2) options for incomplete longitudinal data over time, (3) options for nonlinear changes over time; (4) measurement invariance in studies of changes over time; and (5) new opportunities for modeling dynamic changes. For each issue we will describe the problem, and then review some contemporary solutions to these problems base on Structural Equation Models (SEM). We will fit these SEM to using existing panel data from the Health & Retirement Study (HRS) cognitive variables. This is not intended as an overly technical treatment, so only a few basic equations are presented, examples will be displayed graphically, and more complete references to the contemporary solutions will be given throughout.

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  1. University of Southern California, Los Angeles, CA, 90089, USA

    John J. McArdle

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Presented at: The ZiF Scientific Meeting, Bielefeld, April 2010.

Prepared for Inclusion in: Haupt, H. (2011).

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McArdle, J.J. Longitudinal dynamic analyses of cognition in the health and retirement study panel. AStA Adv Stat Anal 95, 453–480 (2011). https://doi.org/10.1007/s10182-011-0168-z

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