We first define some notation. Let Y denote the response of interest and X denote a p-dimensional vector of covariates. Let T denote a binary indicator of treatment exposure: T = 1 if treated, T = 0 if control. (Yi,Xi, Ti), i = 1, . . . , n, is a random sample from (Y,X, T ). We further define Y (1) as the potential outcome if the subject were treated and Y (0) as the potential outcome if the s...

OBJECTIVES Caring for grandchildren is a common and normative experience for many Chinese grandparents. This study investigates the influence of child care provision on older adults' health trajectories in China. METHOD Using data from the China Health and Nutrition Survey (1991, 1993, 1997, 2000, 2004, and 2006), we apply growth curve models to examine the effect of living arrangements and i...

In cancer observational studies, differences between groups on confounding variables may have a significant effect on results when examining health outcomes. This study demonstrates the utility of propensity score matching to balance a non-cancer and cancer cohort of older adults on multiple relevant covariates. This approach matches cases to controls on a single indicator, the propensity score...

This paper studies the e¤ects of service o¤shoring on the level and skill composition of domestic employment, using a rich data set of Italian …rms and propensity score matching techniques. The results show that service o¤shoring has no e¤ect on the level of employment but changes its composition in favor of high skilled workers.

The aim of this study was to use Monte Carlo simulations to compare logistic regression with propensity scores in terms of bias, precision, empirical coverage probability, empirical power, and robustness when the number of events is low relative to the number of confounders. The authors simulated a cohort study and performed 252,480 trials. In the logistic regression, the bias decreased as the ...

The propensity score methods are widely used to adjust confounding effects in observational studies when comparing treatment effects. The propensity score is defined as the probability of treatment assignment conditioning on some observed baseline characteristics and it provides a balanced score for the treatment conditions as conditioning on the propensity score, the treatment groups are compa...

This issue includes six articles that present logic, methods, and models for causal analyses of observational data, in particular those based on propensity score (PS) methods. The articles include a general introduction to propensity score analysis (PSA), uses of PSA in mediation studies, issues involved in choosing covariates, challenges that often arise in PSA applications, hierarchical data ...

This paper studies the e¤ects of service o¤shoring on the level and skill composition of domestic employment, using a rich data set of Italian …rms and propensity score matching techniques. The results show that service o¤shoring has no e¤ect on the level of employment but changes its composition in favor of high skilled workers.

Empirical evidence from a set of land reform beneficiaries suggests that Zimbabwe’s land reform was successful: the internal rate of return to the land reform project is high, settlers accumulated substantial amounts of assets, and they increased their agricultural productivity substantially over time. This evidence contradicts the general notion that land reform was a failure, a notion support...