In my last post, I showed how to use putexcel to write simple expressions to Microsoft Excel and format the resulting text and cells. Today, I want to show you how to write more complex expressions such as macros, graphs, and matrices. I will even show you how to write formulas to Excel to create calculated cells. These are important steps toward our goal of automating the creation of reports in Excel.
Before we begin the examples, Read more…
I have posted a series of entries about programming an estimation command in Stata. They are best read in order. The comprehensive list below allows you to read them from first to last at your own pace.
- Programming estimators in Stata: Why you should
To help you write Stata commands that people want to use, I illustrate how Stata syntax is predictable and give an overview of the estimation-postestimation structure that you will want to emulate in your programs.
- Programming an estimation command in Stata: Where to store your stuff
I discuss the difference between scripts and commands, and I introduce some essential programming concepts and constructions that I use to write the scripts and commands.
- Programming an estimation command in Stata: Global macros versus local macros
I discuss a pair of examples that illustrate the differences between global macros and local macros.
- Programming an estimation command in Stata: A first ado-command
I discuss the code for a simple estimation command to focus on the details of how to implement an estimation command. The command that I discuss estimates the mean by the sample average. I begin by reviewing the formulas and a do-file that implements them. I subsequently introduce Read more…
Reflecting on the year, Stata has a lot to be thankful for—we released Stata 14, celebrated 30 years of Stata, and had the pleasure of meeting and working with many great people, including our Stata Press authors.
Are you interested in writing a book about Stata or just a book on statistics? We’d love to work with you too. Stata Press offers books with clear, step-by-step examples that make learning and teaching easier. Read more about our submission guidelines, or contact us to get started.
If you’re searching for a good book to read during the holidays, check out our full list of books or our most recent ones below. If you’d like to be notified when new books are released, sign up for Stata Press email alerts.
I hope you all have a great New Year!
Stata for the Behavioral Sciences
Michael N. Mitchell’s Stata for the Behavioral Sciences is an ideal reference for Read more…
I make two improvements to the command that implements the ordinary least-squares (OLS) estimator that I discussed in Programming an estimation command in Stata: Allowing for options. First, I add an option for a cluster-robust estimator of the variance-covariance of the estimator (VCE). Second, I make the command accept the modern syntax for either a robust or a cluster-robust estimator of the VCE. In the process, I use subroutines in my ado-program to facilitate the parsing, and I discuss some advanced parsing tricks.
This is the tenth post in the series Programming an estimation command in Stata. I recommend that you start at the beginning. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series. Read more…
Distributing a Stata command that implements a statistical method will get that method used by lots of people. They will thank you. And, they will cite you!
This post is the first in the series #StataProgramming about programing an estimation command in Stata that uses Mata to do the numerical work. In the process of showing you how to program an estimation command in Stata, I will discuss do-file programming, ado-file programming, and Mata programming. When the series ends, you will be able to write Stata commands.
Stata users like its predictable syntax and its estimation-postestimation structure that facilitates hypothesis testing, specification tests, and parameter interpretation. To help you write Stata commands that people want to use, I illustrate how Stata syntax is predictable and give an overview of the estimation-postestimation structure that you will want to emulate in your programs. Read more…
This post was written jointly with David Drukker, Director of Econometrics, StataCorp.
In our last post, we introduced the concept of treatment effects and demonstrated four of the treatment-effects estimators that were introduced in Stata 13. Today, we will talk about two more treatment-effects estimators that use matching. Read more…
This post was written jointly with David Drukker, Director of Econometrics, StataCorp.
The topic for today is the treatment-effects features in Stata.
Treatment-effects estimators estimate the causal effect of a treatment on an outcome based on observational data.
In today’s posting, we will discuss four treatment-effects estimators:
- RA: Regression adjustment
- IPW: Inverse probability weighting
- IPWRA: Inverse probability weighting with regression adjustment
- AIPW: Augmented inverse probability weighting
We’ll save the matching estimators for part 2.
We should note that nothing about treatment-effects estimators magically extracts causal relationships. As with any regression analysis of observational data, the causal interpretation must be based on a reasonable underlying scientific rationale. Read more…
I want to start a series on using Stata’s random-number function. Stata in fact has ten random-number functions: Read more…
I gave a 1.5 hour talk on Mata at the 2010 UK Stata Users Group Meeting in September. The slides are available in pdf form here. The talk was well received, which of course pleased me. If you’re interested in Mata, I predict you will find the slides useful even if you didn’t attend the meeting. Read more…
I just want to take a moment to plug Statalist. I’m a member and I hope to convince you to join Statalist, too, but even if I don’t succeed, you need to know about the web-based Statalist Archives because they’re a great resource for finding answers to questions about Stata, and you don’t have to join Statalist to access them.
Statalist’s Archives are found at http://www.stata.com/statalist/archive/, or you can click on “Statalist archives” on the right of this blog page, under Links.
Once at the Archives page, you can click on a year and month to get an idea of the flavor of Statalist. More importantly, you can search the archives. The search is Powered by Google and works well for highly specific, directed inquiries. For generic searches such as random numbers or survival analysis, however, I prefer to go to Advanced Search and ask that the results be sorted by date instead of relevance. It’s usually the most recent postings that are the most interesting, and by-date results are listed in just that order.
Anyway, the next time you are puzzling over something in Stata, I suggest that Read more…