Propensity Score-Matching Methods for Nonexperimental Causal Studies

Propensity Score-matching Methods for Nonexperimental Causal Studies

This paper considers causal inference and sample selection bias in nonexperimental settings in which (i) few units in the nonexperimental comparison group are comparable to the treatment units, and (ii) selecting a subset of comparison units similar to the treatment units is difficult because units must be compared across a high-dimensional set of pretreatment characteristics. We discuss the us...

Combining group-based trajectory modeling and propensity score matching for causal inferences in nonexperimental longitudinal data.

A central theme of research on human development and psychopathology is whether a therapeutic intervention or a turning-point event, such as a family break-up, alters the trajectory of the behavior under study. This article describes and applies a method for using observational longitudinal data to make more transparent causal inferences about the impact of such events on developmental trajecto...

Propensity score methods for confounding control in nonexperimental research.

Uncertain Neighbors: Bayesian Propensity Score Matching for Causal Inference

In this paper we compare the performance of standard nearest-neighbor propensity score matching with that of an analogous Bayesian propensity score matching procedure. We show that the Bayesian approach has several advantages, including that it makes better use of available information, since it makes less arbitrary decisions about which observations to drop and which ones to keep in the matche...

Propensity Score Matching for Causal Inference with Relational Data

Propensity score matching (PSM) is a widely used method for performing causal inference with observational data. PSM requires fully specifying the set of confounding variables of treatment and outcome. In the case of relational data, this set may include nonintuitive relational variables, i.e., variables derived from the relational structure of the data. In this work, we provide an automated me...