Our little group at uni is investigating if there is a relationship between 3 measures of social well-being (social anxiety, social connectedness and self esteem) and usage time (on-screen time in hours) on several social media platforms. Would you recommend that we use correlation or regression in this case?

Thanks in advance :)

You need to provide us with more information on your variables, are they categorical or numerical? If usage time is numerical then you can build a linear regression model and the get the coefficients and associated p-values out of it.

If all variables are numerical you could calculate the correlation between them, but the linear model gives more information / is superior.

  • Hi! Thanks for the feedback. All variables are numerical - that is usage time and social well-being measures (questionnaire scores). I guess this means we can build a regression model then? Which one should be the IV and which would be the DV? If we have usage time for multiple social media platforms (9 platforms) and 3 measures for social well-being, will this be multiple regression? – Cafka Sep 14 at 9:25
  • Linear model would be my choice. (FYI Linear models work with both categorical and numerical independent variables and a numerical dependent variable) – user2974951 Sep 14 at 9:28
  • usage time is you DV, the other 3 are your IV's, this is multiple regression. In R lm(usage~v1+v2+v3) – user2974951 Sep 14 at 9:47

If you want to predict things that can't be precisely measured (such as social anxiety, social connectedness, and self esteem) I recommend using your numerical screen time data to perform principal component analysis.

In short, principal component analysis "uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components."

The principal components CAN be interpreted as measurements of something you don't have a measurement for, in this case self esteem, etc... This is a pretty big stretch so if you are doing this in a rigorous academic environment then you are going to need something more to back up your claims.

Read paragraph 2.5 in this paper to see what I mean: http://www.math.montana.edu/jobo/writing/documents/barbour.pdf

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