The aim of this blog is to describe two novel features introduced in Stata 18 (released in 2023): 1) framesets and 2) alias variables across frames. These features enable Stata to deal with a multiplicity of potentially very large datasets efficiently and conveniently. Framesets allow you to bundle, save on file, and load in memory a set of related frames that hold datasets. Alias variables allow you to access variables in other frames as if they were part of the current frame, with very little memory overhead. Read more…
Stata 18 is available now. Visit stata.com/new-in-stata to read all about it.
Major new features include
And there is more.
We are excited about the new features and can’t wait for you to try them out!
Categories: New Products Tags: Bayesian, biostatistics, cox, data science, DID, econometrics, frames, lasso, meta-analysis, new release, RERI, Stata 18, statistics
I have a confession. I wasn’t excited about the addition of frames to Stata 16. Yes, frames has been one of the most requested features for many years, and our website analytics show that frames is wildly popular. Adding frames was a smart decision and our customers are excited. But I have used Stata for over 20 years, and I have been perfectly happy using one dataset at a time. So I ignored frames.
Then I started working on an example for lasso using genetic data. I simulated patient data along with genetic data for each of 22 chromosomes saved in 22 separate datasets. Working with 23 datasets became cumbersome, so I thought I’d check out frames. I began by reading the manual and then tinkered with my genetic data. Along the way, I discovered a feature of frames that completely blew my mind. I’m going to show you that feature below, and I expect that it will blow your mind as well.
This blog post is not meant to be an introduction to frames. There is a detailed introduction to frames in the Stata 16 manual that will make you an expert. I simply want to show you some of the useful things that you can do with frames, including the following: Read more…