Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

Data analyses usually make assumptions (which may be explicit or, more commonly, implicit): for example, “no unmeasured confounding”. When assumptions are untestable their potential importance can ...