Data visualization is a burgeoning field at the crossroads of design, computer science, and statistics. Using HTML and applying data visualization techniques allows the creation of elegant and insightful representations with Stata. Nevertheless, creating original "dataviz" from an empty page is...

Sequence analysis (SA) is a very different way of looking at categorical longitudinal data, such as life-course or labor-market histories (or any ordered categorical data, for that matter). Instead of focusing on transition rates (for example, via hazard rate, Markov or panel models), it takes...

Researchers do not adequately appreciate that floating-point numbers are a simulation of real numbers and, as with all simulations, some features are preserved while others are not. When writing code, or even do-files, treating the computer's floating-point numbers as if they were real numbers...

More efficient trial designs are needed to combat the increasing cost of drug development. A class of trial designs that can help to accelerate this process, known as multi-arm multi-stage (MAMS) designs, has been proposed and used to much effect in oncology. To facilitate the design of these...

The Bayesian approach to statistical analysis has many theoretical advantages, but in the past, its use has been limited by a lack of suitable statistical software. In a book published this year by Stata Press called Bayesian Analysis with Stata, I have tried to show that Stata can be used for...

The Cox proportional hazards model is one of the most popular methods for analyzing survival or failure-time data. The key assumption underlying the Cox model is that of proportional hazards. This assumption may often be violated in practice. Transformation survival models extend the Cox...

This paper presents a parametric counter-factual model identifying average treatment effects (ATEs) by conditional mean independence when externality (or neighborhood) effects are incorporated within the traditional Rubin-potential outcome model. As such, it tries to generalize the usual...

The time-stratified case-crossover design is widely used in environmental epidemiology to analyze the short-term effects of environmental risk factors, such as air pollution or temperature, on human health. It compares the exposure level in the day when the health event occurs (case day) with...

So-called non-parametric methods are in fact based on estimating and testing parameters, usually either rank parameters or spline parameters. Two comprehensive packages for estimating these are somersd (for rank parameters) and bspline (for spline parameters). Both of these estimate a wide range...

The avar routine (Baum and Schaffer, SSC) constructs the "filling" for a number of flavors of "sandwich" covariance matrix estimators, including HAC, one- and two-way clustering, common cross-panel autocorrelated errors, etc. We show how avar can be used as a building block to construct VCEs...