Confounding is a major consideration in etiological investigation because it can result in biased estimation

of exposure effects. Control of confounding in data analysis is achieved by stratified analysis or by multivariable analysis. (Control of confounding in research design stage is achieved by matching for observational studies and by randomization for experimental studies.) Stratified analysis is accomplished by stratifying the confounding variable into homogeneous categories and evaluating the association within these strata. Multivariable analysis, on the other hand, involves the use of a regression model and allows the researcher to control for all confounders at the same time while looking at the contribution of each risk factor to the outcome variable. Stratified analysis is a necessary preliminary step to performing regression modeling to control for confounding. ...

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