Causation of bias: The episcope

A risk ratio or difference from a meta-analysis is as many as ten steps awa y from the unobservable causal risk ratios and differences in target popula tions. The steps are like lenses, filters, or other fallible components of the epidemiologist's "telescope" for observing populations. Each step is an other domain where different biases can be caused. How biases combine acros s domains in the production of epidemiologic evidence can be quickly explai ned to nonepidemiologists by using a sequence of causal arrow diagrams with easy notation: (a) agent of interest, (b) background risk factors, (c) cor related causes, (d) diagnosis, (e) exposure measurement, (f) filing of data , (g) grouping of cohorts, (h) harvesting of cases and controls, (i) interp retations of investigators, (j) judgments of journals, and (k) knowledge of meta-analysts. For epidemiologists, this article serves as a review of ide as about confounding, information bias, and selection bias and underscores the need for routinely analyzing the sensitivity of study findings to multi ple hypothesized biases.