I think this is the most clear explanation of confounding I have heard. Also an excellent example of why diabetes would likely not be a confounder in relation to obesity - CHD. Thank you!
So, in general, we adjust for confounders to make two groups comparable in all other way BUT the primary exposure? (can it be worded like this?). Secondly- lets say we take another variable - nicotine patch use. Lets say it satisfies the definition (3-criteria based) on confounding. But what if we do not have data about that at all?! What if the researchers did not collect any information regarding a certain potential confounder? What would we do in that case? Please let me know. Thanks
I think this is the most clear explanation of confounding I have heard. Also an excellent example of why diabetes would likely not be a confounder in relation to obesity - CHD. Thank you!
Great Epidemiologist, thanks so much
So, in general, we adjust for confounders to make two groups comparable in all other way BUT the primary exposure? (can it be worded like this?). Secondly- lets say we take another variable - nicotine patch use. Lets say it satisfies the definition (3-criteria based) on confounding. But what if we do not have data about that at all?! What if the researchers did not collect any information regarding a certain potential confounder? What would we do in that case? Please let me know. Thanks
Thank you very much. But why did not you upload the RCT or experimental study
He said "86%" but I think he meant 86 to mean the # of people in that category
Big help Professor 👍
Wonderful lecture
Great video , thanks sir