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...

Stratification is a sampling design that can improve efficiency. It works by first partitioning the population into homogeneous subgroups and then performing simple random sampling within each group. For a continuous variable, stratification involves determining strata boundaries. Holding the...

Dong and Lewbel have developed the theory of simple estimators for binary choice models with endogenous or mismeasured regressors, depending on a `special regressor' as defined by Lewbel (J. Econometrics, 2000). `Control function' methods such as Stata's ivprobit are generally only valid when...

This talk exemplifies the application of the multiple imputation technique available in STATA to analize a design of experiments with multiple responses and missing data. No imputation and multiple imputation methodologies are compared.

This presentation introduces a set of Stata programs designed to match individuals from year-to-year in the Current Population Survey (CPS) using a distance based measure of similarity . Unlike panel data, the CPS is a repeated cross section of geographic residences, which are continually...

As the title implies, EFA within a CFA framework combines aspects of both EFA and CFA. It uses CFA to produce a factor solution that is close to an EFA solution while providing features typically found in CFA, such as, standard errors, statistical tests and modification indices. The presentation...

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...

The main purpose of this work is to discuss Stata’s capability to implement customized likelihood functions compared with Gauss’s. I compare these two high-level programming languages with built-in function libraries and graphic routines. Overall, Stata’s features seem best suited for...

In this talk, I will discuss the main methodological features of the bivariate dynamic probit model for panel data. I will present an example using simulated data, giving special emphasis to the initial conditions problem in dynamic models and the difference between true and spurious state...

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...