In this talk, I will provide an overview of Stata features that are typically used for the analysis of psychometric and educational testing data. Traditional multivariate tools such as canonical correlation, MANOVA, multivariate regression, Cronbach’s alpha, exploratory and confirmatory...

This study brings together Census block-level data on broadband service availability, economics, demographics, regulations, and terrain to model the supply and demand of high-speed broadband service in the United States. While Stata is the primary tool for data management and multilevel...

In this talk, I will give a brief introduction to structural equation modeling (SEM) and Stata’s sem command. I will also introduce the SEM Builder—the graphical user interface for drawing path diagrams, fitting structural equation models, and analyzing the results. Using the SEM...

In Agricultural Economics 37 (2007) 201–210, using a counterfactual outcomes framework, Diagne and Demont showed that observed sample technological adoption rate does not consistently estimate the population adoption rate even if the sample is random. Likewise, it is shown that a model of...

This talk introduces two Stata routines to implement the non-parametric heteroskedasticity and autocorrelation consistent (SHAC) estimator of the variance–covariance matrix in a spatial context, as proposed by Conley (1999) and Kelejian and Prucha (2007). The (SHAC) estimator is robust...

The growing popularity of alternative choices to traditional-based public schools—such as public charter/lottery-based schools—has prompted nationwide research. In Anchorage, however, there are few quantitative studies that compare student performance across traditional public...

With a view towards lessening the analytic and computational burden faced by practitioners seeking to correct the standard errors of two-stage estimators, we offer a heretofore unnoticed simplification of the conventional formulation for the most commonly encountered cases in empirical...

In this presentation, the author presents a procedure and an illustrative application of a user-written Allocation Model(AE) in Stata. AE measures allocative efficiency and economic efficiency as well as technical efficiency when price and cost information of production are available. This model...

Estimating the density of a distribution from a finite number of data points is an important tool in the statistician's and data analyst's toolbox. In their recent paper, Bernacchia and Pigolotti (JRSS-B, 2011) introduce a new non-parametric method for the density estimation of univariate...

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...