We explore the potential benefit of using higher-order moments in the balancing conditions for covariate-balancing propensity scores and entropy balance.
The study used statistical methods designed to approximate RCTs when comparing more than two nonequivalent groups that include an assessment of the potential impact of omitted variables in order to address potential dosage effects for a commonly used evidence based substance use treatment program for adolescents.
This tutorial demonstrates the use of the Toolkit for Weighting and Analysis of Nonequivalent Groups Shiny application for time-varying treatments -- for cases when the time-varying treatment or exposure is binary -- using an illustrative example.
This document provides a brief tutorial on using the twangContinous package to estimate causal effects for continuous exposure variables using generalized propensity scores estimated via generalized boosted models.
In this tool, the authors explain the methodology behind the primary function of the selection bias decomposition (SBdecomp) package; describe its features, syntax and how to implement the function; and illustrate its use with an example.
This paper introduces a new approach to estimating the propensity score using Gaussian processes and optimizing hyperparameters with respect to covariate balance.
This discussion highlights potentially meaningful ways to optimize propensity score machine learning methods to allow for minimal bias and less variability.
This tutorial describes the use of the TWANG package in R to estimate inverse probability of treatment weights (IPTWs) when one has time varying treatments or sequences of treatments over time.
Contrary to popular belief, having a dog or cat in the home does not improve the mental or physical health of children. There's no evidence to support the notion that pets can improve child health by increasing physical activity and improving empathy skills.
The use of propensity scores to control for pretreatment imbalances on observed variables in non-randomized or observational studies examining the causal effects of treatments or interventions has become widespread over the past decade.
There is a bias-variance tradeoff at work in propensity score estimation; every step toward better balance usually means an increase in variance and at some point a marginal decrease in bias may not be worth the associated increase in variance.
Addresses the role race plays a role in officers' use of discretion in traffic stops by proposing a technique to determine the extent to which race bias affects citation rates, search rates, and the duration of the stop.
Propensity score weights estimated using boosting eliminate most pretreatment group differences and substantially alter the apparent relative effects of adolescent substance abuse treatment.