Matching is employed to control for confounding variables that could distort the true association between the exposure and the outcome. By ensuring that cases and controls are similar in terms of these confounders, researchers can more accurately isolate the effect of the exposure of interest. This method is especially useful when dealing with variables that are strongly related to both the exposure and the outcome.
