R has many ways to store information. Most of the time, our data comes in the form of a dataset, which we bring into R as a data.frame object. However, there are times when we want to use matrices as well. This post will show you how matrices can...
Blog Archives
Extracting Information From Objects Using Names()
One of the big differences between a language like Stata compared to R is the ability in R to handle many different types of objects at once, and combine them together or pull them apart. I had a post about objects last year, but I thought I'd sh...
Normal distribution functions
Ah, the Central Limit Theorem. The basis of much of statistical inference and how we get those 95% confidence intervals. It's just so beautiful! Lately, I have found myself looking up the normal distribution functions in R. They...
Converting a dataset from wide to long
I recently had to convert a dataset that I was working with from a wide format to a long format for my analysis. I struggled with this a bit, but finally found the right sources and the right package to do it, so I thought I'd share my practical ...
Translating Weird R Errors
I love R. I think it's intuitive and clever and overall a great language. But I do get really annoyed sometimes at the completely ridiculous, cryptic error messages it often gives me. This post will go over some of those seemingly nonsensical err...
For loops (and how to avoid them)
My experience when starting out in R was trying to clean and recode data using for() loops, usually with a few if() statements in the loop as well, and finding the whole thing complicated and frustrating.In this post, I'll go over how you can avoi...
Basics of Histograms
Histograms are used very often in public health to show the distributions of your independent and dependent variables. Although the basic command for histograms (hist()) in R is simple, getting your histogram to look exactly like you want takes g...
Data types part 4: Logical class
First, an update: A commentator has asked me to post my code so that it is easier to practice the examples I show here. It will take me a little bit of time to get all of my code for past posts well-documented and readable, but I have uploa...
Data types, part 3: Factors!
In this third part of the data types series, I'll go an important class that I skipped over so far: factors.Factors are categorical variables that are super useful in summary statistics, plots, and regressions. They basically act like dummy variables t...
Data types part 2: Using classes to your advantage
Last week I talked about objects including scalars, vectors, matrices, dataframes, and lists. This post will show you how to use the objects (and their corresponding classes) you create in R to your advantage.First off, it's important to remember...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
