Semiparametric regression deals with the introduction of some very general nonlinear functional forms in regression analyses. This class of regression models is generally used to fit a parametric model in which the functional form of a subset of the explanatory variables is not known and/or in...

In the robust statistics literature, a wide variety of models has been developed to cope with outliers in a rather large number of scenarios. Nevertheless, a recurrent problem for the empirical implementation of these estimators is that optimization algorithms generally do not perform well when...

When some observations are outlying (in one or several dimensions) PCA is distorted an may lead to incorrect results. We therefore propose a simple solution to deal with this problem by providing a short ado file. To illustrate the importance of outliers in PCA I would like to present a simple...

In regression and multivariate analysis, the presence of outliers in the dataset can strongly distort classical estimations and lead to unreliable results. To deal with this, several robust-to-outliers methods have been proposed in the statistical literature. In Stata, some of these methods are...

The creation and testing of interaction terms in regression models can be very cumbersome, even in Stata 8. We propose a simple wrapping command, -fitint-, that fits any generalised linear model and tests any twoway interactions, as well as all main effects. There is no need to use -xi- because...

Among various structures in Stata for cycling through lists (whether lists of variable names, numbers, or arbitrary strings) are foreach and forvalues, introduced in Stata 7 in 2001, and for, introduced in Stata 3.1 in 1992, and revised in 5.0 (1997) and 6.0 (1999). Typically, each member of the...

I research the market efficiency of the German 6/49 parimutuel lottery game using Stata. To this end, I investigate the existence of profit opportunities for particularly unpopular combinations of numbers (Papachristou and Karamanis (1998)), employing the covariates proposed by Henze and Riedwyl...

A Stata program will be presented for improved quality control of econometric models. It is well known that reported econometric results often have unknown reliability because of selective reporting by the researcher. In particular, t-statistics are often uninformative or misleading when...

Stata's matrix language, Mata, highlighted in Bill Gould's Mata Matters columns in the Stata Journal, is very useful and powerful in its interactive mode. Stata users who write do-files or ado-files should gain an understanding of the Stata-Mata interface: how Mata may be called upon to do one...

Literature on causal inference has emphasized the average causal effect, defined as the mean difference in potential outcomes under different treatment conditions. We consider marginal regression models that describe how causal effects vary in relation to covariates. To estimate parameters, we...