How to control confounding effects by statistical analysis
نویسندگان
چکیده
A Confounder is a variable whose presence affects the variables being studied so that the results do not reflect the actual relationship. There are various ways to exclude or control confounding variables including Randomization, Restriction and Matching. But all these methods are applicable at the time of study design. When experimental designs are premature, impractical, or impossible, researchers must rely on statistical methods to adjust for potentially confounding effects. These Statistical models (especially regression models) are flexible to eliminate the effects of confounders.
منابع مشابه
Alternatives to randomisation in the evaluation of public-health interventions: statistical analysis and causal inference.
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