Given the BRFSS dataset with hundreds of variables, is it possible for me to check one explanatory variable causing the other, or just a correlation between the two? [Explained in text]

Link to the variables list. Suppose I hypothesize that lack of sleep causes an increase in heart attack rates. I have a plethora of variables in my dataset – arthritis, blood sugar, cholestrol etc – some of which may affect heart attack rates and some may not. Is there a way I can say for sure that lack of sleep CAUSES heart attack rate increase, or, because of these other variables I can only point out a correlation between the two? After all, there could be a confounding variable linking these two right? ​ This is a part of a course project I’m pursuing, if anyone wanted to know. Also, English isn’t a native language, sorry if I made grammatical errors! (Please critique my terminology as well here, I’m a newcomer to the field so I may not use the terms correctly.) submitted by /u/Akainu18448 [link] [comments]

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Nevin Manimala

Nevin Manimala is interested in blogging and finding new blogs

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