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...

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...

Econometricians have begun to devote more attention to spatial interactions when carrying out applied econometric studies. The new command we are presenting, xsmle, fits fixed- and random-effects spatial models for balanced panel data for a wide range of specifications: the spatial...

We propose an estimator for models in which an endogenous dichotomous treatment affects a count outcome in the presence of either sample selection or endogenous participation using maximum simulated likelihood. We allow for the treatment to have an effect on both the participation or the sample...

When I first met Stata in October 2000, my golf handicap was 27 and my game was going nowhere slowly. Ten years of intensive Stata therapy later, my handicap is 17.3 and falling. It would, of course, be nonsense to infer from this data that lowering your handicap increases Stata use, but could...

I present the new Stata 12 command, mi impute chained, to perform multivariate imputation using chained equations (ICE), also known as sequential regression imputation. ICE is a flexible imputation technique for imputing various types of data. The variable-by-variable specification of ICE allows...

Functions in Stata range between those you know you want and those you don't know you need. The word "functions" is heavily overloaded in Stata; here the focus is on functions' strict sense, _variables, extended macro functions, and egen functions. Often Stata users in difficulty are seeking...

Background: Random effects are commonly modeled in multilevel, longitudinal, and latent-variable settings. Rather than estimating fixed effects for specific clusters of data, "predictions" can be made as the mode or mean of posterior distributions that arise as the product of the random effect...

Modern genetic genome-wide association studies typically rely on single nucleotide polymorphism (SNP) chip technology to determine hundreds of thousands of genotypes for an individual sample. Once these genotypes are ascertained, each SNP alone or in combination is tested for association...

Splines, including polynomials, are traditionally used to model nonlinear relationships involving continuous predictors. However, when they are included in linear models (or generalized linear models), the estimated parameters for polynomials are not easy for nonmathematicians to understand, and...