OBJECTIVES
Selection bias is a well‐known concern in research on older adults. We discuss two common forms of selection bias in aging research: (1) survivor bias and (2) bias due to loss to follow‐up. Our objective was to review these two forms of selection bias in geriatrics research. In clinical aging research, selection bias is a particular concern because all participants must have survived to old age, and be healthy enough, to take part in a research study in geriatrics.
DESIGN
We demonstrate the key issues related to selection bias using three case studies focused on obesity, a common clinical risk factor in older adults. We also created a Selection Bias Toolkit that includes strategies to prevent selection bias when designing a research study in older adults and analytic techniques that can be used to examine, and correct for, the influence of selection bias in geriatrics research.
RESULTS
Survivor bias and bias due to loss to follow‐up can distort study results in geriatric populations. Key steps to avoid selection bias at the study design stage include creating causal diagrams, minimizing barriers to participation, and measuring variables that predict loss to follow‐up. The Selection Bias Toolkit details several analytic strategies available to geriatrics researchers to examine and correct for selection bias (eg, regression modeling and sensitivity analysis).
CONCLUSION
The toolkit is designed to provide a broad overview of methods available to examine and correct for selection bias. It is specifically intended for use in the context of aging research.
from Wiley: Journal of the American Geriatrics Society: Table of Contents http://bit.ly/2IWAYOI
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