[email protected]

You can install and load **tab** from GitHub via the following code:

The main purpose of **tab** is to create neatly formatted summary tables for papers and presentations. The following functions are included:

`glm_v`

prints a GLM summary table to the RStudio Viewer`tabglm`

summarizes generalized linear models (GLM’s) fit via`glm`

or`survey::svyglm`

`tabgee`

summarizes generalized estimating equation models (GEE’s) fit via`gee::gee`

`tabcoxph`

summarizes Cox Proportional Hazards models fit via`survival::coxph`

or`survey::svycoxph`

`tabmulti`

compares variables across two or more groups, e.g. to create a “Table 1”`tabmulti.svy`

does the same thing as`tabmulti`

but for complex survey data

To summarize a fitted generalized linear model, simply call `glm_v`

as you would `glm`

. The result will be a formatted summary table printed to the RStudio Viewer. Here’s an example for logistic regression:

From here, you can “snip” the summary table and save it as a figure (as I did for this README) or copy directly from the Viewer and paste outside of R.

For more flexibility, see `tabglm`

. That function lets you control things like what columns to present, how categorical predictors are presented, and so on.

You can use `tabmulti`

to summarize variables across two or more groups, using a formula interface. Here’s an example:

The functions all return `kable`

objects, so they should work perfectly well in R Markdown and knitr documents.

Xie, Yihui. 2014. “Knitr: A Comprehensive Tool for Reproducible Research in R.” In *Implementing Reproducible Computational Research*, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC. http://www.crcpress.com/product/isbn/9781466561595.

———. 2015. *Dynamic Documents with R and Knitr*. 2nd ed. Chapman; Hall/CRC.

———. 2021. *Knitr: A General-Purpose Package for Dynamic Report Generation in R*.