For a statistics task I've been given a data set (regarding drugs prevention) and a few questions. One of the questions is to check whether or not the choice of treatment, treatment A or treatment B, impacts the odds of staying drugsfree. We're told to be cautionous of possible confounders, like a having history of intravenous drugs use.
Now, my problem is, I'm not really sure how to check if this has an impact or not, and even less sure how to keep the confounders in mind.
The given variables in the dataset are: Age, beck depression score, history of IV drug use (never, in the past or recently, number of prev. treatments, race, duration of treatment (long/short), which treatment (A/B), and whether or not they were still drugsfree after 12 months.
Any help is welcome.
Checking whether or not a variable has impact
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statistics
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0You might have a better chance getting this answered at [CV](http://stats.stackexchange.com/). – 2012-08-13
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Assuming you are probably using multicollinear regression - if you remove a variable and can still produce a strong multicollinear model, the variable you removed may be a confounding variable, or it may be insignificant.