Because impact evaluation is an important tool that guides public policy decisions and because applying impact evaluation is a rigorous process, we must generate examples of how impact evaluation methodologies apply to the Mexican context. To this end, we have used nonexperimental methodologies...

Some surveys collect data of individuals who are nested within hierarchical organizations or countries. These data are useful, for instance, for ranking countries according to a major outcome adjusted for covariates. Reporting only means produces rankings that are biased. So it is necessary to...

Searches for genes using linkage analyses with genetic markers placed across the entire human genome are hypothesis-free experiments, which represent an extreme form of multiple testing. As such, the low p-values required to obtain nominal significance make accurate diagnostics essential to...

The Stata command xtreg estimates the random-effects linear regression model, for which the random effects are assumed to be normally distributed with zero mean and non-negative variance, s^2_{i,t}. Testing homogeneity across units is equivalent to testing the null hypothesis H_0: s^2_{i,t} = 0,...

Stata's graphics are more flexible than many realise. We will exploit this flexibility and explore a potpourri of topics, some of interest to all graphers and others primarily of interest to those creating highly customised graphs or new graph commands. Among the topics will be creating custom...

In medical prognosis based on survival analysis, there is an interest in visualizing the shape of the hazard function. In fully parametric models, the shape of the hazard function is constrained by the properties of the chosen distribution (Weibull, log-logistic, lognormal, Gompertz, gamma). The...

Longitudinal studies in which exposures, confounders and outcomes are measured repeatedly over time have the potential to allow causal inferences about the effects of exposure on outcome. There is particular interest in estimating the causal effects of medical treatments (or other interventions)...

Following the seminal publications of Rubin starting about 30 years ago, statisticians have become increasingly aware of the inadequacy of `complete case' analysis of datasets with missing observations. In medicine, for example, observations may be missing in a sporadic way for different...

In the presence of dependent competing risks in survival analysis, the Cox proportional hazards model can be utilised to examine covariate effects on the cause-specific hazard function for each type of failure. The method proposed by Lunn and McNeil (1995) requires data augmentation. With k...

This paper introduces the dhurdle command for Stata, a maximum-likelihood routine ( d2) to estimate the Cragg double hurdle model with either independent or dependent errors. We give a brief description of the procedure and its application to durable goods consumption and market participation...