EPI 201 Summary 2 [Confounding] A source of bias that distorts the true measure of association and is something that we aim to eliminate from our study. [Impact of confounding on validity] In the presence of confounding, the point estimate is biased (Confounding introduce bias into point estimates) => The results of statistical inferential procedures such as p values and confidence intervals are biased. => p-value: too small or too large, CI: centered (bias in the point estimate) or width (bias in the estimate of the variance of the point estimate) The magnitude of the bias due to confounding in an epidemiologic study depends on: ・ The association between the confounder and the outcome ・ The ratio of prevalence of the confounder in the exposed group divided by the prevalence of the confounder in the unexposed group ・ The prevalence of the confounder Downward bias: the association appears more protective ∴ after adjustment, the association will be higher on the absolute value, closer to the null and it may even indicate a harmful association
[Example of confounding] Crude Odds Ratio Smoking and MI Prevalence Ratio Crude OR is biased toward upward direction. DM No DM Total MI 122 1490 1612 No MI 31 1581 1612 Total 153 3071 3224 Smoking No Smoking Total MI 500 990 1490 No MI 155 1426 1581 Total 655 2416 3071 DM No DM Total Smoker 15 155 170 No Smoker 16 1426 1442 Total 31 1581 1612
[Matching on Case-control study] ・ Matching on case-control study leads to confounding (selection bias) ・ Matching on factors that are likely to be confounders can improve the efficiency of the study. ・ Once the data are stratified on the confounding factor, there will be balance between the number of cases and controls within each stratum. [Alteration for the association between the confounder and the exposure of interest in the study] ・ Matching in a cohort study ・ Restriction: (restriction to women => no confounder about gender) ・ Selection criteria ・ Randomization [Matching on confounders in a cohort study] 1: Prevalence of the matching factors (confounders) is the same in the exposed and unexposed. 2: eliminate the confounfer-exposure association × matching in a case control study (lead to selection bias)
In a case-control study, the controls are used to estimate the exposure distribution on the study base. Matching may cause the exposure distribution among the controls to no longer represent the exposure distribution in the study base. Thus one must also adjust for the matching factors in the analysis stage. ○ un-matching, but selection [Selection criteria] [95% CI] The data are consistent with odds ratios between A and B, with 95% confidence.
[Effect measure modification] ・ Effect measure modifier − In the presence of effect measure modification, the magnitude of the association between exposure and disease varies according to a third factor, called an effect modifier.
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- Fall '18