January. Is. Over. Though the world is on fire/everything is spiders, in my work-life, I am quite relieved: I have escaped the most gruelling month of continuos large deadlines that I’ve ever had to manage (#NewFacultyLife), while (mostly) getting everything done that I needed to. Hurray!
So now that I am entering a month when I will encounter the thing-of-myth referred to as, free time, I wanted to quickly hammer out a blog post to start getting back in the swing of posting more regularly. With that, it’s a new MIP post, this time focusing on making DIY “Pirate Plots”.
I’m back with a new Make It Pretty post. I’ve been quietly thrilled with how well my other two Make It Pretty posts have done. My post on visualizing various 2-way interactions (easily my most popular not-current-issue post) has been viewed over 1000 times, and more excitingly, is now the top hit if you google “2-way interaction ggplot2”. And though much less popular, I’m still happy with the ~300 views my meta-analysis visualizations post (on forest and funnel plots) has attracted–I even saw one of my funnel plots in the ‘wild’ shortly after! With this post, I’m going to be showing how you can use the psych package in conjunction with ggplot2 in order to create a prettier scree plot with parallel analysis–a very useful visualization when conducting exploratory factor analysis. Continue reading →
By now, I’ve made it pretty clear: I absolutely love the ggplot2 package for plotting visualizations of data. In fact, I’m pretty sure I’m addicted. But in the last couple of years, I’ve discovered another love–meta-analysis. Meta-analyses are often accompanied by two popular forms of data visualization: forestplots and funnel plots. In this post, I’ll show how quick-and-dirty forest and funnel plots can be created with the metafor package. After, I’ll show how we can instead use the ggplot2 package to create forest plots and use the ggplot2 package to create funnel plots, so that we can have pretty plots that are easy to change/stylize, and that can be produced regardless of which meta-analysis package for R that you elect to use. Continue reading →
ggplot2, as I’ve already made clear, is one of my favourite packages for R. And since that original post about ggplot2 remains one of my most frequently visited, I thought I would proceed with starting a series of posts called “Make It Pretty”, all about sharing ways of visualizing data that I think are attractive/effective/comprehensive. So with this inaugural MIP post, I will be covering how to plot 2-way interactions using ggplot2. Continue reading →
I am a frequent R user, but this wasn’t always the case. Though I have had R installed on my computer for about four years now, it has only been in the last year and a half that I turned a corner and began to use R on the near-daily. The ggplot2 package was a huge reason why, and I think if you are looking to become a more regular R user too, ggplot2 is a fantastic place to start. Continue reading →