I tried to include the summary of an lm
object in an Rmd file, using code like the following but it didn\'t work. Could you help me do that?
```
The $$
syntax only applies to math expressions, and you were trying to put a table in it, which will not work. The apsrtable
, as far as I understand, is for LaTeX only, but LaTeX and Markdown are very different -- there is little hope you can redo LaTeX entirely with Markdown. I think people invented the $$
syntax for Markdown due to the fact that it is well supported by MathJax, and also note there are many variants/flavors based on the original Markdown.
At the moment you may consider:
xtable
or ascii
or R2HTML
package to generate HTML tablesapsrtable
to support HTML tablesCross-posting my answer to Table of multiple lm() models using apsrtable in Rmarkdown:
It can be done in a pdf_document
with apsrtable and also stargazer, which additionally supports HTML.
---
title: "stargazer"
author: "hplieninger"
date: "3 August 2018"
output: pdf_document
header-includes:
- \usepackage{dcolumn}
---
```{r}
m1 <- lm(Fertility ~ Education , data = swiss)
m2 <- lm(Fertility ~ Education + Agriculture, data = swiss)
m3 <- lm(Fertility ~ . , data = swiss)
```
```{r, results='asis'}
apsrtable::apsrtable(m1, m2, m3, Sweave = TRUE)
```
```{r, results='asis'}
# If output: pdf_document
stargazer::stargazer(m1, m2, m3)
# If output: html_document
# stargazer::stargazer(m1, m2, m3, type = "html")
```
What about including my_model
in Markdown format with `pander˙:
> library(pander)
> pander(my_model)
--------------------------------------------------------------
Estimate Std. Error t value Pr(>|t|)
----------------- ---------- ------------ --------- ----------
**x** 0.1174 0.1573 0.7465 0.4767
**(Intercept)** -0.2889 0.9759 -0.296 0.7748
--------------------------------------------------------------
Table: Fitting linear model: y ~ x
Or in PHP MarkdownExtra/rmarkdown format:
> panderOptions('table.style', 'rmarkdown')
> pander(my_model)
| | Estimate | Std. Error | t value | Pr(>|t|) |
|:-----------------:|:----------:|:------------:|:---------:|:----------:|
| **x** | 0.1174 | 0.1573 | 0.7465 | 0.4767 |
| **(Intercept)** | -0.2889 | 0.9759 | -0.296 | 0.7748 |
Table: Fitting linear model: y ~ x