Any analysis with incomplete data makes untestable assumptions about the missing data, and analysts are therefore urged to conduct sensitivity analyses. Ideally, a model is constructed containing a nonidentifiable parameter d, where d = 0 corresponds to the assumption made in the standard...

In this talk we describe how to fit structural mean models (SMMs), as proposed by Robins, using instrumental variables in the generalized method of moments (GMM) framework using Stata's gmm command. The GMM approach is flexible because it can fit overidentified models in which there are more...

Stata already has an extensive range of built-in and user-written commands for analyzing xt (cross-sectional time-series) data. However, most of these commands do not take into account important features of the data relating to their time-series properties or cross-sectional dependence. This...

Measurement error in exposure variables can lead to bias in effect estimates, and methods that aim to correct this bias often come at the price of greater standard errors (and so, lower statistical power). This means that standard sample size calculations are inadequate and that, in general,...

Multiple imputation (MI) is known as an effective method for handling missing data. However, it is not clear that the method will be effective when the data contain a high percentage of missing observations on a variable. This study examines the effectiveness of MI in data with 10% to 80%...

Econometricians have begun to devote more attention to spatial interactions when carrying out applied econometric studies. In part, this is motivated by an explicit focus on spatial interactions in policy formulation or market behavior, but it may also reflect concern about the role of omitted...

In this presentation, I provide a detailed discussion of an alternative iterative approach for the estimation of linear regression models with two high-dimensional fixed-effects, such as large employer-employee datasets. I also show how to extend the approach to three high-dimensional fixed...

Clinical trial statistical analysis and reporting is a formidable task. A final-study report requires the creation of hundreds of tables and data listings, and the calculation of over one thousand statistical significance levels, difference estimates, and confidence limits. Typically, several...

In recent times, due to developments in the field of information economics, there was a rationalization of the link between financial factors and fluctuations in economic activity (Bernanke et al. 1996; Gertler 1988). An issue that has been highlighted is the possibility that fluctuations in...

Much more investment will be needed in developing countries to achieve the Millennium Development Goals, specifically, the goal of reducing poverty. In this respect, private-sector investment is critical, bringing more funds, expertise, and efficiency to the development of projects in several...