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I have a data frame (df) where I see correlation between two continuous variables (c1 and c2). I need to know whether the observed correlation between the two variables differs between groups, which are identified with a categorical variable (v1)?

I tried to find interaction using lm function in R. I tried lm(c1~c2*v1,data=df) and looked for p value of the interaction c2:v1. I am not sure if this is correct. Please correct me if I am wrong.

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I think you should implement a Sperman correlation (by group).

See this link, to another stackexchange.com question.

In alternative, see this other link, to another stackexchange.com question.

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  • $\begingroup$ Thank you for those links. But I also need to know if the correlations obtained by factors are statistically different. Any comment on that? $\endgroup$
    – Veera
    Commented Jul 2, 2015 at 6:30
  • $\begingroup$ Doesn't R give you p-values as well? That's what you should look at. $\endgroup$
    – Fuca26
    Commented Jul 2, 2015 at 6:35
  • $\begingroup$ I meant if I get correlation in subset1 is 0.4 and subset2 is 0.6, I need to know if correlation in subset1 is statistically different from correlation in subset2. Hope you get me. $\endgroup$
    – Veera
    Commented Jul 2, 2015 at 6:37
  • $\begingroup$ Lets say I am looking for the correlation between the blood insulin and glucose levels in a group of participants. Suppose if i need to know how the correlation varies, if i group them in to diabetics and non-diabetics, what should I do. $\endgroup$
    – Veera
    Commented Jul 2, 2015 at 6:49
  • $\begingroup$ I have tried to clarify your question. Roll it back if you do not like it or distort the meaning of your initial question. $\endgroup$
    – Fuca26
    Commented Jul 2, 2015 at 6:51

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