In large observational studies there are often significant differences between characteristics of a treatment group and a no treatment group. Such differences should not exist in a randomized trial. These differences must be adjusted for in order to reduce treatment selection bias and determine treatment effect. There are several methods to reduce the bias of these differences and make the two ...

Nutritional labeling has been of much interest to policy makers and health advocates due to rising obesity trends. So can nutritional label use really help reduce body weight outcomes? This study evaluates the impact of nutritional label use on body weight using the propensity score matching technique. We conducted a series of tests related to variable choice of the propensity score specificati...

The propensity score is a common tool for estimating the causal effect of a binary treatment using observational data. In this setting, matched methods, defined as either individual matching, subclassifying, or using inverse probability weighting on the propensity score, can reduce the initial covariate bias between the treatment and control groups. With more than two treatment options, however...

A recent survey of 54 micro-econometric studies reveals that exporting firms are more productive than non-exporters. On the other hand, previous empirical studies show that exporting does not necessarily improve productivity. One possible reason for this result is that most previous studies are restricted to analysing the relationship between a firm’s export status and the growth of its labour ...

When randomized experiments cannot be conducted in practice, propensity score (PS) techniques for matching treated and control units are frequently used for estimating causal treatment effects. Despite the popularity of PS techniques, they are not yet well studied for matching multilevel data where selection into treatment takes place at the lowest level. Two main strategies for matching level-...

This research examines whether lower-income married renters are more likely to become homeowners than comparable single renters. Using data from the Community Advantage Panel Study, we use discrete-time survival analysis with propensity score matching to explore this relationship. Results indicate married couples have higher odds of buying a home, and do so at faster rates, than their unmarried...

Instrumental variables (IVs) are used to control for confounding and measurement error in observational studies. They allow for the possibility of making causal inferences with observational data. Like propensity scores, IVs can adjust for both observed and unobserved confounding effects. Other methods of adjusting for confounding effects, which include stratification, matching and multiple reg...

Background: Lithium has been reported in some, but not all, studies to be associated with reduced suicide risk. Methods: Intention-to-treat, high-dimensional propensity score-matched cohort study of one-year suicide mortality in Veterans Health Administration patients (n = 21,194/treatment) initiating lithium or valproate from 1999-2008. One-year suicide mortality was examined among all patient...

Sensitivity of Propensity Score Methods to the Specifications Propensity score matching estimators have two advantages. One is that they overcome the curse of dimensionality of covariate matching, and the other is that they are nonparametric. However, the propensity score is usually unknown and needs to be estimated. If we estimate it nonparametrically, we are incurring the curse-of-dimensional...

We use multiple longitudinal data sources and propensity score matching to assess the long-term outcomes of the Neighborhood Transformation Initiative (NTI) in the Sandtown-Winchester community of Baltimore. This comprehensive community initiative, implemented in the 1990s, remains one of the most well-known urban revitalization projects in the country, due to its significant funding (more than...