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I have trouble understanding the regression output that I created for my beginners class of R. I use two binary variables and ask whether the fact that someone volunteers raises hers or his life satisfaction. I am familiar with the interpretation of numeric variables as "increase in X leads to decrease in Y". But how do I interpret binary variables? How do I handle the fact that X is not statistically significant while Y is?

This might be more of a Stackoverflow question: Should/Can I change the coding so that it examines the effect of people which are volunteering (volunteeryes)?

regression output

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  • $\begingroup$ Is your outcome variable binary (e.g., satisfied/unsatisfied) or a rating of life satisfaction? $\endgroup$
    – Dave
    Commented Mar 8, 2022 at 11:24
  • $\begingroup$ Just like you guessed its satisfied/unsatisfied. Input is volunteering yes/no (in this case: no) $\endgroup$
    – Blattla
    Commented Mar 8, 2022 at 11:33
  • $\begingroup$ Please type your question as text, do not just post a photograph or screenshot (see here). When you retype the question, add the self-study tag & read its wiki. Then tell us what you understand thus far, what you've tried & where you're stuck. We'll provide hints to help you get unstuck. Please make these changes as just posting your homework & hoping someone will do it for you is grounds for closing. $\endgroup$
    – kjetil b halvorsen ♦
    Commented Mar 8, 2022 at 12:02

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The intercept is the log odds of life satisfaction of the group that volunteers. Unsurprisingly, this group has a mean life satisfaction that is statistically significantly different from zero (not exactly as many satisfied and unsatisfied people).

The “volunteerno” parameter is the amount by which the log-odds of life satisfaction differs among people who do not volunteer. This is not significantly different from the mean life satisfaction of people who do volunteer.

Depending on how you view the world, you may find it surprising or upsetting that people tend not to be satisfied with their lives (negative log odds means a low probability of life satisfaction).

I would conclude that there is more to the probability of life satisfaction than volunteering (job, romance, successful children, etc). However, this study does not give evidence that volunteering contributes, with the usual caveats about interpreting large p-values and causality.

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  • $\begingroup$ Thank you so much for this explanation. Still, some terms are too abstract for my understanding. If my assumption is that people who volunteer are more satisfied with life, this output would suggest the opposite since the intercept estimate is negative? $\endgroup$
    – Blattla
    Commented Mar 8, 2022 at 12:03
  • $\begingroup$ The intercept is a raw value, not compared to anything. The interpretation is that more people who volunteer are unsatisfied with life than satisfied. This could be for any number of reasons (e.g., COVID, or maybe life is just hard and people tend not to be satisfied). $\endgroup$
    – Dave
    Commented Mar 8, 2022 at 12:24

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