Louisa H. Smith
Multiple-Bias Sensitivity Analysis Using Bounds
We show that it is possible to bound the total composite bias due to unmeasured confounding, selection, and differential misclassification, and to use that bound to assess the sensitivity of a risk ratio to any combination of these biases.
Selection Mechanism and Their Consequences: Understanding and Addressing Selection Bias
Understanding the way in which a study sample relates to the target population is critical for avoiding and addressing bias. Communication about selection bias is aided by the use of causal graphs.
Simple Sensitivity Analysis for Control Selection Bias
We extend a sensitivity analysis approach for selection bias to account for poor control selection in case-control studies.
Bounding Bias Due to Selection
We provide bounds for selection bias under a variety of situations.