In real world observational research, two basic components of any study are exposure and outcome. In absence of randomization, bias occurs when a measure of association between exposure and outcome is systematically wrong. Selection bias, misclassification and confounding are typical problems that must be faced by the researcher so that a causal unbiased association between exposure and outcome is estimated. Knowing and understanding these issues is the first step for fighting them, armed with the powerful weapons of study design and statistical analysis.
Speaker: Fabio Ferri, Medineos Epidemiology and Outcome Research Specialist
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