The new rmarkdown revolution has started. The image is CC by Jonathan Cohen.
The new R Markdown (rmarkdown-package) introduced in Rstudio 0.98.978 provides some neat features by combining the awesome knitr-package and the pandoc-system. The system allows for some neat simplifications of the fast-track-publishing (ftp) idea using so called formats. I’ve created a new package, the Grmd-package, with an extension to the html_document format, called the docx_document. The formatter allows an almost pain-free preparing of MS Word compatible web-pages.
In this post I’ll (1) give a tutorial on how to use the docx_document, (2) go behind the scenes of the new rmarkdown-package and RStudio ≥ 0.98.978, (3) show what problems currently exists when skipping some of the steps outlined in the tutorial. Continue reading →
A forest plot using different markers for the two groups
In order to celebrate my Gmisc-package being on CRAN I decided to pimp up the
forestplot2 function. I had a post on this subject and one of the suggestions I got from the comments was the ability to change the default box marker to something else. This idea had been in my mind for a while and I therefore put it into practice. Continue reading →
Putting all the pieces together can be challenging both for surgeons and researchers. The image is CC by Zac Peckler
Fast-track publishing using knitr is a short series on how I use knitr to speedup publishing in my research. There has been plenty of feedback and interest for the series, and in this post I would like to provide (1) a brief summary and (2) an example showing how to put all the pieces together. Continue reading →
Constructing tables is an art – maximizing readability and information can be challenging. The image is of the Turning Torso in Malmö and is CC by Alan Lam.
Fast-track publishing using knitr is a short series on how I use knitr to speedup publishing in my research. While illustrations (previous post) are optional, tables are not, and this fourth article is therefore devoted to tables. Tables through knitr is probably one of the most powerful fast-track publishing tools, in this article I will show (1) how to quickly generate a descriptive table, (2) how to convert your regression model into a table, and (3) worth knowing about table design and anatomy. Continue reading →
Images can be a powerful medium if used right. The image is CC by alemdag.
Fast-track publishing using knitr is a short series on how I use knitr to speedup publishing in my research. This is the third article in the series devoted to plots. Hopefully you will through this post have the need-to-know stuff so that you can (1) add auto-numbering to your figures, (2) decide on image formats, (3) choose image resolution, and (4) get anti-aliasing working. Continue reading →
Flexing RStudio/knitr where you want can be a challenge. The image is CC by Ben Barnes.
Fast-track publishing using knitr is a short is a short series on how I use knitr to get my articles faster published. This is part II where I will show how you can tweak RStudio into producing seamless MS Word-integration by using the .RProfile together with CSS, a few basics about HTML that might be good to know, and lastly some special characters that can be useful. In the previous post, part I, I explained some of the more general concepts behind fast-track publishing and why I try to get my manuscript into MS Word instead of using LaTeX or other alternatives. Continue reading →
A beautiful old document. Probably state of the art in those days. The image is CC by storebukkebruse.
Fast-track publishing using knitr is a short series on how I use knitr to get my articles faster published. By fast-track publishing I mean eliminating as many of the obstacles as possible during the manuscript phase, and not the fast-track some journals offer. In this first introductory article I will try to (1) define the main groups of obstacles I have experienced motivating knitr, (2) options I’ve used for extracting knitted results into MS Word. The emphasis will be on general principles and what have worked for me. Continue reading →
A forestplot that compares Swedish and Danish EQ-5D outcome predictors generated with the forestplot2()-function in the Gmisc-package
Displaying large regression models without overwhelming the reader can be challenging. I believe that forestplots are amazingly well suited for this. The plot gives a quick understanding of the estimates position in comparison to other estimates, while also showcasing the uncertainty. This project started with some minor tweaks to prof. Thomas Lumleys forestplot and ended up in a complete remake of the function. In this post I’ll show you how to tame the plot using data from my latest article. Continue reading →
Harvesting the magical update() function. The image is CC by Waldemar Horwat.
The key to programming is being lazy; it has actually been called a virtue by some. When I discovered the update() function it blew me away. Within short I had created a monster based upon this tiny function, allowing quick and easy output of regression tables that contain crude and adjusted estimates. In this post I’ll show you how to tame the printCrudeAndAdjusted() function in my Greg-package and show a little behind the scenes. Continue reading →
A transition between states – the above is a simulation of before and after surgery where I’ve highlighted the large proportion that doesn’t improve in the moderate group.
As an orthopaedic surgeon I’m often interested in how a patient is doing after surgery compared to before. I call this as a transition between states, e.g. severe pain to moderate pain, and in order to better illustrate these transitions I’ve created something that I call a transition plot. It’s closely related to the plotMat for plotting networks but aimed at less complex relations with only a one-way relation between two groups of states.
This project started by me posting a question on Stack Overflow, the answers were (as always) excellent, but didn’t really satisfy my needs. What I wanted was a graphically appealing plot that I could control in extreme detail. Thanks to Paul Murrell’s excellent grid package I was able to generate a truly customizeable transition plot.
In this post I’ll give a short introduction with examples to what you can do with the transitionPlot()-function. I’ll try to walk you through simple transitions to more complex ones with group proportions and highlighted arrows. Continue reading →