Without statistical adjustment, the associations observed in a study may be misleading due to the influence of confounders. For example, in a study examining the relationship between smoking and lung cancer, failing to adjust for age could result in an overestimation or underestimation of the true effect of smoking. Statistical adjustment helps to mitigate this bias, ensuring that the observed association is as close to the true association as possible.
