Measurement error in explanatory variables and unmeasured confounders can cause
considerable problems in epidemiologic studies. It is well recognized that under certain …

Epidemiologists are aware that the estimated effect of an exposure can be biased if the
investigator fails to adjust for confounding factors when analyzing either a prospective or …

PURPOSE: Uncontrolled confounders are an important source of bias in epidemiologic
studies. The authors review and derive a set of parallel simple formulas for bias factors in the …

It is common to present multiple adjusted effect estimates from a single model in a single
table. For example, a table might show odds ratios for one or more exposures and also for …

Procedures to correct estimates of association in epidemiologic studies for the effects of
exposure measurement error have rarely been employed in practice. The application of …

Confounding is recognized as a mixing of effects that can lead to spurious conclusions
about the association between disease and a putative risk factor. Confounding occurs if an …

This paper presents a general approach for assessing the sensitivity of the point and interval
estimates of the primary exposure effect in an observational study to the residual …

A relative risk estimate which relates an exposure to risk of disease will tend to be estimated
too close to unity if that exposure is subject to random measurement error or intra-subject …

Greenland first documented (Am J Epidemiol 1980; 112: 564–9) that error in the
measurement of a confounder could resonate—that it could bias estimates of other study …

To correct for confounding, the method of instrumental variables (IV) has been proposed. Its
use in medical literature is still rather limited because of unfamiliarity or inapplicability. By …