Methodological Challenges in Causal Research on Racial and Ethnic Patterns of Cognitive Trajectories: Measurement, Selection, and Bias |
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Authors: | M Maria Glymour Jennifer Weuve Jarvis T Chen |
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Institution: | (1) Department of Society, Human Development, and Health, Harvard School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA;(2) Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA;(3) Department of Internal Medicine, Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, IL, USA;(4) Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA |
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Abstract: | Research focused on understanding how and why cognitive trajectories differ across racial and ethnic groups can be compromised
by several possible methodological challenges. These difficulties are especially relevant in research on racial and ethnic
disparities and neuropsychological outcomes because of the particular influence of selection and measurement in these contexts.
In this article, we review the counterfactual framework for thinking about causal effects versus statistical associations.
We emphasize that causal inferences are key to predicting the likely consequences of possible interventions, for example in
clinical settings. We summarize a number of common biases that can obscure causal relationships, including confounding, measurement
ceilings/floors, baseline adjustment bias, practice or retest effects, differential measurement error, conditioning on common
effects in direct and indirect effects decompositions, and differential survival. For each, we describe how to recognize when
such biases may be relevant and some possible analytic or design approaches to remediating these biases. |
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Keywords: | Causal research Racial and ethnic disparities Cognitive trajectory Neuropsychological research Counterfactuals Directed acyclic graphs Measurement error Selection |
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