Partial correlation with multiple control variables

// Partial correlation with multiple control variables //

This video shows how to conduct a partial correlation given a third variable in R.

Remember, that partial correlation measures the degree of association between two variables, controlling for other associated variables, in this case only one additional variable.

I'll show conducting a partial correlation with the convenient ppcor-package and its pcor()-function. It is necessary aforehand to remove cases with missing values, which I will also show.
Finally, you can compare the bivariate correlation with the partial correlation and see if the correlation increased, decreased or remained the same, when controlling for a third variable.

Example
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In my example I want to correlation IQ and income and want to control for the association of each with age and motivation.

⏰ Timestamps:
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0:00 Introduction
0:05 Prerequisites
0:37 Using pcor() for partial correlation
1:02 Interpreting partial correlation results

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Support channel? 🙌🏼
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Thank you for your support! ♥

[vipulwagh]

Hey, thanks for the tutorial. So, would data from the 3rd column onwards be treated as confounding variables in this function?

[a.sparkle]

Hi! Great Tutorial! Thanks a lot! Can you do the same for a semi partial correlation? So conducting a semi partail correlation controlled for multiple other variables?