How to plot several regression lines in same scatter plot in R?

Question

I have a dataframe with data of body temperature (Tb), substrate temperature (Ts) for several individuals of both sexes and comming from three different populations like this: (I made up this table since I couldn't manage to share my full table, but I have around 30 individuals from each pop) ``` pop sex tb ts bo m 37 30 bo m 39 29 bo f 36 36 pa m 40 34 pa f 37 28 pa m 37 33 pa f 36 26 re f 35 24 re f 37 29 re m 38 30 ``` I want to assess the relationship between Tb and Ts but not only for the species but for each population separately in order to identify possible differences in slopes among them. ``` my.regression <- lm(tb ~ ts*pop*sex, data = mydata) ``` I managed to plot a scatter plot with different colors, one byeach of my populations. However, I couldn't plot my regressions lines. I searched for answers everywhere: about how to add the regression lines by group...(not in stackoverflow, not even with the help of almighty google, youtube tutorials, R book, R graphics books and so…

Accepted Answer

This is easy to do using ggplot2 and a geom_smooth layer:

```
library(ggplot2)
ggplot(mydata, aes(x=tb, y=ts, col=pop)) + geom_point() +
            geom_smooth(method="lm", se=FALSE)
```

If you want to separate by sex as well, then as suggested by @Henrik you might want to try placing them in separate subgraphs (called facets):

```
ggplot(mydata, aes(tb, ts, col=pop)) + geom_point() +
             geom_smooth(method="lm", se=FALSE) + facet_wrap(~ sex)
```

Alternatively you could plot by both of them, but use the line type (solid or dashed) to distinguish sex:

```
ggplot(mydata, aes(tb, ts, col=pop, lty=sex)) + geom_point() +
             geom_smooth(method="lm", se=FALSE)
```

How to plot several regression lines in same scatter plot in R?

Solution

Problem