Some remarks on the operation of biases.

Etiologic research is easily invalidated by wrong conclusions based on the use of dubious methods of study design or data analysis. This paper discusses three central types of validity concepts, namely, selection bias, information bias, and confounding bias. Bias is defined in statistical terms as a misrepresentation of an effect measure, such as disease rate ratio. The discussion is presented basically within the framework of fourfold frequency table data to investigate the dependence of the presence or absence of a disease on a dichotomous exposure variate. A brief review of the statistical strategies and techniques available for controlling confounding is given. The issue of properly measuring a true confounder is dealt with in some detail because of its importance for the avoidance of biased estimates. The presentation concentrates on pointing out the direction and magnitude of the distortion caused by the operation of these sources of error.