Selection Bias

Selection bias in epidemiological studies occurs when study participants do not accurately represent the population for whom results will be generalized, and this results in a measure of association that is distorted (i.e., not close to the truth). For example, if persons responding to a survey tend to be different (e.g., younger) than those who do not respond, then the study sample is not representative of the general population, and study results may be misleading if generalized. You should be able to explain how potential biases might influence the reported results and their interpretation. Knowing how to analyze selection biases in reported research or your own studies allows you to assess to which populations results can be generalized, as well as to understand possible distortions in the measures of association. This can guide the application of evidence-based practice as well as your own research agenda.

 

For this Discussion, review the article(below). Consider issues surrounding selection bias, and the effects that selection bias may have on study results.

Describe what selection bias is. Explanation of the types of selection bias that might have occurred in the study. Explain how the researchers minimized these types of bias in the study, either through study design or analysis considerations. Finally, describe the effects these biases could have had on the interpretation of study results if not minimized.

Chae, D., Nuru-Jeter, A., Lincoln, K., & Jacob Arriola, K. (2012). Racial discrimination, mood disorders, and cardiovascular disease among Black Americans. Annals of Epidemiology, 22(2), 104-111.

 

 

 

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