POPM 3240 Lecture Notes - Lecture 2: Causal Inference, Confounding, Reporting Bias
8 Dec 2016
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Identify and discuss the potential effects of common biases observed in epidemiological research including: Define and discuss disease causation, statistical associations and causal inference and rank common study designs by their ability to establish causality. Any systematic error in the design, conduct or analysis of a study that results in a mistaken estimate of an exposure"s effect on the risk of disease. Bias differs from random error because it is systematic in nature. Simply increasing the size of a sample will not address bias. Some strategies to address bias include careful study design, randomization, and appropriate statistical approaches. Error is defined as a deviation from true values. Importantly, there are three types of bias we want you to know: selection bias. As shown in figure 2. 2, each type of bias has a predominant effect at each and every stage of the research process. It is important to consider, evaluate, and address all forms of bias within a study.
