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...

Simulation studies are conducted to assess novel and currently used methods in practice, to better assess and understand the frameworks under question. In survival analysis, we are interested in simulating both an event and a censoring distribution to better reflect clinical data. In this talk,...

Treatment changes in randomized trials are common: for example, in a trial evaluating psychotherapy, individuals allocated to psychotherapy may attend only partially or not at all; or in a trial evaluating a drug treatment, individuals allocated to no drug treatment may nevertheless receive the...

This presentation describes a Stata implementation of a space-filling location selection algorithm. The objective is to select a subset from a discrete list of locations so that the spatial coverage of the locations by the selected subset is optimized according to a geometric criterion. Such an...

Graphical display of regression results has become increasingly popular in presentations and the scientific literature because, in many cases, graphs are much easier to read than tables. In Stata, such plots can be produced by the marginsplot command. However, while marginsplot is very versatile...

The boxplot is probably the most commonly used tool to represent the distribution of the data and identify atypical observations in a univariate dataset. The problem with the standard boxplot is that as soon as asymmetry or tail heaviness appears, the percentage of values identified as atypical...

Good graphics often exploit one simple graphical design that is repeated for different parts of the data, which Edward R. Tufte dubbed the use of small multiples. In Stata, small multiples are supported for different subsets of the data with by() or over() options of many graph commands; users...

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...