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.

Even experienced data analysts can get off track, especially with large data sets with many variables. It's just so easy to try different versions of models or get distracted by interesting, but irrelevant, relationships among variables. The lesson? Make a plan.

Item Response Theory (IRT) refers to a family of statistical models for evaluating the design and scoring of psychometric tests, assessments and surveys. It is used on assessments in psychology, psychometrics, education, health studies, marketing, economics and social sciences — assessments that involve categorical items (e.g., Likert items).

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, […]

Item Response Theory (IRT) refers to a family of statistical models for evaluating the design and scoring of psychometric tests, assessments and surveys. It is used on assessments in psychology, psychometrics, education, health studies, marketing, economics and social sciences — assessments that involve categorical items (e.g., Likert items).

Sometimes it's because the dependent variable just isn't appropriate for a GLM. The dependent variable, Y, doesn't have to be normal for the residuals to be normal (since Y is affected by the X's). But Y does have to be continuous, unbounded, and measured on an interval or ratio scale.

There’s a common saying among pediatricians: children are not little adults. You can’t take a drug therapy that works in adults and scale it down to a kid-sized treatment. Children are actively growing. Their livers metabolize drugs differently, and they have a stage of life called puberty that many of us have long forgotten. Likewise, […]

Many variables we want to measure just can’t be directly measured with a single variable. Instead you have to combine a set of variables into a single index. But how do you determine which variables to combine and how best to combine them? Exploratory Factor Analysis.

Level is a statistical term that is confusing because it has multiple meanings in different contexts (much like alpha and beta). There are three different uses of the term Level in statistics that mean completely different things. What makes this especially confusing is that all three of them can be used in the exact same […]