It has been suggested that children’s savings programs will be more effective if they are combined with strategies to build children’s college-bound identities. In this study we use a multi-level treatment approach to propensity score analysis to test this proposition. Findings suggest that children who have savings and are certain they will graduate from a four-year college are more likely to ...

Often, when conducting programme evaluations or studying the effects of policy changes, researchers may only have access to aggregated time series data, presented as observations spanning both the pre- and post-intervention periods. The most basic analytic model using these data requires only a single group and models the intervention effect using repeated measurements of the dependent variable...

The paper evaluates the effect of the FAMEX export promotion program in Tunisia on the export performance of beneficiary firms using firm-level data. Propensity-score matching difference-indifference and weighted least squares estimates suggest that beneficiaries expand at the intensive and the extensive margin (markets and products). However, this expansion is short-lived for total exports. Ou...

Propensity-score matching is increasingly being used to reduce the confounding that can occur in observational studies examining the effects of treatments or interventions on outcomes. We used Monte Carlo simulations to examine the following algorithms for forming matched pairs of treated and untreated subjects: optimal matching, greedy nearest neighbor matching without replacement, and greedy ...

The propensity score plays a central role in a variety of causal inference settings. In particular, matching and weighting methods based on the estimated propensity score have become increasingly common in the analysis of observational data. Despite their popularity and theoretical appeal, the main practical difficulty of these methods is that the propensity score must be estimated. Researchers...

Abstract Propensity scores represent the probability that an individual is assigned to a treatment group given the individual’s scores on a set of covariates. Propensity scores are used in nonrandomized studies to equate treatment and control groups on a large number of covariates measured at baseline. Assumptions necessary for propensity score analysis to yield a valid estimate of t...

BACKGROUND The results of two randomized phase 3 trials that investigated the use of laquinimod in patients with relapsing-remitting multiple sclerosis were analyzed using a propensity score model. METHODS The propensity score in each study was defined as the probability of an individual patient being assigned to either the laquinimod or placebo study arm. The analysis included two main stage...

Propensity score analysis is a relatively recent statistical innovation that is useful in the analysis of data from quasi-experiments. The goal of propensity score analysis is to balance two non-equivalent groups on observed covariates to get more accurate estimates of the effects of a treatment on which the two groups differ. This article presents a general introduction to propensity score ana...