From the last post in this series, you should know how to change between numeric types and easily change numeric data. We’ll now expand your type-changing skills to include changing string variables with two new commands. (more…)
From the last post in this series, you should know how to change between numeric types and easily change numeric data. We’ll now expand your type-changing skills to include changing string variables with two new commands. (more…)
From our last posts in this series, you should be comfortable with how Stata handles data editing, as well as with making your own variables. In this post, we’ll talk about commands that edit the content or storage type of your variables in Stata: recode and recast. Let’s start off with the recode command.
From our last article, you should feel comfortable with the idea of editing and saving data sets in Stata. In this article, we’ll explain how to create new variables in Stata using replace, generate, egen, and clonevar.
Stata makes it a breeze to edit or clean your data. If you’re unfamiliar with using data sets in Stata, check out these blog posts to get a good grasp on importing and browsing data in Stata.
For this tutorial we will be using Stata’s “auto” data set. If you haven’t loaded it in yet, type
There’s no mincing words here. Missing values can cause problems for every statistician. That’s true for a lot of reasons, but it can start with simple issues of choices made when coding missing values in a data set. Here are a few examples.
Researcher Joseph Tartaro thought it would be funny to get the following California vanity license plate: (more…)
Survey questions are often structured without regard for ease of use within a statistical model.
Take for example a survey done by the Centers for Disease Control (CDC) regarding child births in the U.S. One of the variables in the data set is “interval since last pregnancy”. Here is a histogram of the results.