Research-Related Resources

Using R has really benefitted my career a lot. It lets you have a reproducible workflow that other programs (cough cough, SPSS) just don’t really allow for. You can take a raw dataset all the way to publication-ready figures and tables, all in R, and have a perfect, reproducible record of it all. After a while, R also just allows you to accomplish tasks so much faster than SPSS (and also doesn’t take 13.5 years to open up to start). But, when you first start using R, the vast majority of tasks could actually be done much faster in SPSS. And given how busy we all are, I totally get why people would want to do the thing that saves them the most time! So I won’t discourage that. Use R for what it’ll help you with, and make the switch gradually. That’s what I did, and I tell everyone to do it that way.

So I thought one useful thing to do with my website is to put up resources about using R specifically for psychological scientists. I’m no data scientist (though if no academic institutions offer me a tenure-track job in a few years, I very well might become one…), so I’d be entirely unsurprised if you start using my materials and then discover a much faster/easier way to do what I’ve shown. That’s okay! There’s always like 20 ways to do something in R and arrive at the correct answer. So make use of my code if it’s useful to you, and if it’s not, just don’t mention it to me so my ego stays inflated.

Training/mentoring is very important to me personally, so if you are trying to teach someone else R (e.g., your grad students or undergrad RAs) and can’t figure out how to accomplish the analysis you are trying to do, please feel free to contact me and I will try my best to help you figure it out!

Undergrad/Postbacc Module 1

How to think like a scientist.

Undergrad/Postbacc Module 2

Info on broad psychopathology dimensions.

Undergrad/Postbacc Module 3

Crash courses on specific forms of psychopathology, and how basic dispositional traits relate to psychopathology.

Undergrad/Postbacc Module 4

A very brief introduction to common statistical concepts.

R Tutorial 1

Intro/Loading Data in to R

R Tutorial 2

Data wrangling and other R tips.

R Tutorial 3

Doing common statistics in R - correlations, t-tests, anova/ancova, and multiple regression.

R Tutorial 4

Making Figures in R. Time for some ggplot!

R Tutorial 5

Doing more advanced statistics in R - Intro to Latent Variable Modeling.