Consideration of confounding is fundamental to the design, analysis, and interpretation of studies intended to estimate causal effects. Unfortunately, the word confounding has been used synonymously with several other terms, and it has been used to refer to at least four distinct concepts. This paper provides an overview of confounding and related concepts based on a counterfactual model of causation. In this context, which predominates in nonexperimental research, confounding is a source of bias in the estimation of causal effects. Special attention is given to the history of definitions of confounding, the distinction between confounding and confounders, problems in the control of confounding, the relations of confounding to exchangeability and collapsibility, and confounding in randomized trials.