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The challenge of selection bias and confounding in palliative care research
Helene Starks1, Paula Diehr, J Randall Curtis
1Department of Bioethics and Humanities, School of Medicine, University of Washington, Seattle, WA 98195-7120, USA. tigiba@u.washington.edu
Journal of Palliative Medicine
|February 12, 2009
Abstract
No abstract available in PubMed .
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Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...
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Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
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