for example, we have 3 confounding random variables, x1, x2 and x3 with 3 different variances. If we had to treat each variable alone, we would have used odd ratio or relative risk ( depending on what kind of study we are using whether retrospective or prospective) to determine the risk of the disease given the variable. What if we have 3 variables? how can we combine all of them to the get the odd ratio of diagnosing the disease? Do we have to use logistic regression analysis with the logit as a linear combination function of multiple variables? Also what does it have to do with our specific patient who comes with a combination of x1, x2 and x3, do we have to plug those values into the logistic analysis in order to get the probability of having the disease?(adsbygoogle = window.adsbygoogle || []).push({});

To complicate the issue ( although it is not neccessarily at this stage), what if we conduct a metaanalysis with different studies are conducted at different places, how would we combine those data into a the result?

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# Dealing with multiple confounding variables

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