Adding lm summaries to plots RStudio

Question

I'm using this tutorial to perform a linear regression. Is there a way to add the summary (results) of the linear model to the plot in order to save it as a pdf.

This is the code:

scatter.smooth(x=cars$speed, y=cars$dist, main="Dist ~ Speed")  # scatterplot


linearMod <- lm(dist ~ speed, data=cars)  # build linear regression model on full data
print(linearMod)

#> Call:
#> lm(formula = dist ~ speed, data = cars)
#> 
#> Coefficients:
#> (Intercept)        speed  
#>     -17.579        3.932





summary(linearMod)  # model summary
#> Call:
#> lm(formula = dist ~ speed, data = cars)
#> 
#> Residuals:
#>     Min      1Q  Median      3Q     Max 
#> -29.069  -9.525  -2.272   9.215  43.201 
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)    
#> (Intercept) -17.5791     6.7584  -2.601   0.0123 *  
#> speed         3.9324     0.4155   9.464 1.49e-12 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Residual standard error: 15.38 on 48 degrees of freedom
#> Multiple R-squared:  0.6511, Adjusted R-squared:  0.6438 
#> F-statistic: 89.57 on 1 and 48 DF,  p-value: 1.49e-12

Answer 1

What you want to do is surprisingly difficult, which is why most people would not choose to do it that way :)

The closest solution I could find uses ggplot2 and a lot of other packages. It's possible to do the following:

1. Create a summary table of the regression model using stargazer::stargazer()
2. Convert that to a PNG image file using kableExtra::as_image()
3. Convert the PNG to a grob using grid::rasterGrob()
4. Use ggplot2::annotation_custom() to embed the table-as-image-as-grob into a ggplot2 chart

Note that as_image() requires some other packages and an installation of phantomjs.

Here's an example:

However, there are other solutions that might be better such as a simple summary using ggpubr::stat_regline_equation() or adding a table grob using the output of broom::tidy().

I think the simplest way to demonstrate all the options is in a RMarkdown file. Here is the code to copy into an RMarkdown file which you can knit in RStudio.

---
title: "Regression"
author: "Neil Saunders"
date: "27/01/2021"
output:
  html_document: 
    toc: yes
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE,
                      message = FALSE,
                      fig.path = "figures/")
library(ggplot2)
library(ggpubr)
library(broom)
library(gridExtra)
library(kableExtra)
library(grid)
library(sjPlot)
library(stargazer)
library(png)

theme_set(theme_bw())
```

# The model
```{r echo=TRUE}
linearMod <- cars %>% 
  lm(dist ~ speed, data = .)
```

# Visualizations

## Add equation and adjusted R-squared to a plot
```{r}
cars %>% 
  ggplot(aes(speed, dist)) +
  geom_point() +
  geom_smooth(method = "lm") +
  stat_regline_equation(
    aes(label =  paste(..eq.label.., ..adj.rr.label.., sep = "~~~~"))
  )
```

## Add tidy summary table to a plot
```{r}
linearMod_tidy <- tidy(linearMod)

cars %>% 
  ggplot(aes(speed, dist)) +
  geom_point() +
  geom_smooth(method = "lm") +
  annotation_custom(tableGrob(linearMod_tidy, 
                    theme = ttheme_default(base_size = 10)), 
                    xmin = 0, ymin = 90)
```


## Add tabular summary and plot side-by-side
### stargazer

:::::: {.columns}
::: {.column width="48%" data-latex="{0.48\textwidth}"}
```{r}
cars %>% 
  ggplot(aes(speed, dist)) +
  geom_point() +
  geom_smooth(method = "lm")
```
:::
::: {.column width="4%" data-latex="{0.04\textwidth}"}
\ 
<!-- an empty Div (with a white space), serving as
a column separator -->
:::
:::::: {.column width="48%" data-latex="{0.48\textwidth}"}
```{r results='asis'}
stargazer(linearMod, type = "html")
```
:::
::::::

### tab\_model

:::::: {.columns}
::: {.column width="48%" data-latex="{0.48\textwidth}"}
```{r echo=FALSE,}
cars %>% 
  ggplot(aes(speed, dist)) +
  geom_point() +
  geom_smooth(method = "lm")
```
:::
::: {.column width="4%" data-latex="{0.04\textwidth}"}
\ 
<!-- an empty Div (with a white space), serving as
a column separator -->
:::
:::::: {.column width="48%" data-latex="{0.48\textwidth}"}
```{r}
tab_model(linearMod)
```
:::
::::::

## Add stargazer table to a plot

```{r}
imgfile <- stargazer(linearMod, type = "html") %>% 
  as_image()

img <- readPNG(imgfile)
g <- rasterGrob(img, interpolate = TRUE, width = 0.5, height = 0.5)

cars %>% 
  ggplot(aes(speed, dist)) +
  geom_point() +
  geom_smooth(method = "lm") +
  annotation_custom(g, xmin = 1, xmax = 15, ymin = 50, ymax = 130)
```