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.
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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.
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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
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There are two main types of factor analysis: exploratory and confirmatory. 
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Binary logistic regression is one of the most useful regression models. It allows you to predict, classify, or understand explanatory relationships between a set of predictors and a binary outcome.
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How do you know if the items of a test are hard or easy; fair or biased; accurate at measuring ability or not? 
Item Response Theory (IRT).
In this training, you will see, with real life examples, how IRT answers these questions to assess a test.
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