In an era in which doctors and patients aspire to personalized medicine and more sophisticated risk estimation, detecting and modeling interactions between covariates or between covariates and treatment is increasingly important. In observational studies (for example, in epidemiology),...

Propensity score matching has become a popular empirical method because of its capability of reducing the dimensionality of finding comparable units to conditioning on a scalar quantity. The validity of this approach relies on the balancing property of the propensity score. In practice, this is...

We present the Stata package stgenreg for the parametric analysis of survival data. Any user-defined hazard or log hazard function can be specified, with the model estimated using maximum likelihood utilizing numerical quadrature. Standard parametric models (for example, the Weibull proportional...

Visualizing the true effect of a predictor over a range of values can be difficult for models that are not parameterized in their natural metric, such as for logistic or (even more so) probit models. Interaction terms in such models cause even more fogginess. In this talk, I show how both the...

How to plot (and summarize) univariate distributions is a staple of introductory data analysis. Graphical (and numerical) assessment of marginal and conditional distributions remains important for much statistical modeling. Research problems can easily evoke needs for many comparisons, across...

Much interest has been focused on animated graphical displays of data in recent years, although this mostly involves some expertise with specialized software and programming. There is a lack of simple tools for data analysts to use to produce animations. In this presentation, I will show how...

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...

In a 2012 article in the Journal of Business & Economic Statistics, Arthur Lewbel presents the theory of allowing the identification and estimation of "mismeasured and endogenous regressor models" by exploiting heteroskedasticity. These models include linear regression models customarily...

This presentation shows a somewhat complex automatization scheme in Stata that was developed during preparation of two papers using firm-level data and applying the propensity score matching techniques to distill the direct effects of the presence of foreign investors on various indicators from...

Following in the footsteps of the Stata user-written command ivtreatreg, recently proposed by the author (Cerulli, 2012), the paper presents a new Stata routine— contreatreg—for estimating a Dose Response Treatment Model under continuous treatment endogeneity and heterogeneous...